A TALE of TWO IRESES

A TALE of TWO IRESES:

TRANSLATIONAL REGULATION MEDIATED BY

THE EUKARYOTIC FMR1 AND AURORA A IRESES IN DISEASE

TARA HEATHER WEILAND DOBSON

B.A., Metropolitan State College of Denver, 1996

A thesis submitted to the

Faculty of the Graduate School of the

University of Colorado in partial fulfillment

of the requirements for the degree of

Doctor of Philosophy

Biochemistry and Molecular Genetics Program

2012

This thesis for the Doctor of Philosophy degree by

Tara Heather Weiland Dobson

has been approved for the

Biochemistry and Molecular Genetics Program

James DeGregori, Chair

Heide Ford

Jeffery Kieft

Sandra Martin

Robert Sclafani

Leslie A. Krushel, Advisor

Date 11/21/12

Dobson, Tara Heather Weiland (Ph.D., Biochemistry and Molecular Genetics)

A Tale of Two IRESes: Translational Regulation Mediated by the Eukaryotic FMR1 and Aurora A IRESes in Disease

Thesis directed by Associate Professor Leslie A. Krushel

ABSTRACT

Regulation of translation initiation of most eukaryotic mRNAs occurs in a cap- dependent manner. In this study I demonstrate how misregulated translation of two eukaryotic mRNAs via internal ribosomal entry sites (IRESes) contributes to two otherwise unrelated diseases.

The 5’leader of the FMR1 gene contains high guanosine/cytosine nucleotide content, including the CGG trinucleotide repeats associated with Fragile X Syndrome.

The focuses of my study were to confirm and extend a previous observation that the

FMR1 5' leader contains an IRES. A combination of reporter assays did confirm the

FMR1 5' leader contains an IRES. Moreover, inhibiting cap-dependent translation ex vivo did not affect the expression level of endogenous FMRP indicating a role for IRES- dependent translation of FMR1 mRNA. Analysis of the leader revealed that the CGG repeats and the 5' end of the leader were vital for internal initiation. Functionally, exposure to mimics of neural activity and double stranded RNA differentially affected

FMR1 IRES activity. My results indicate that multiple stimuli influence FMR1 IRES activity and suggest a functional role for the CGG nucleotide repeats.

Many mechanisms, from DNA amplification to protein stability, can contribute to over-expression of the Aurora A oncoprotein in cancers. My study identified a novel mechanism that autonomously leads to Aurora A over-expression in numerous epithelial

iii cell lines compared to primary cells. The Aurora A gene can be alternatively spliced resulting in transcripts encoding for the same protein but containing varying 5’ leaders.

ApppG capped RNA assays revealed four leaders with enhanced IRES activity in Aurora

A over-expressing cells. Characterization of these leaders identified IRES elements in exons Ib, II, and IIa. The exon Ib IRES was active in primary and immortalized cell lines.

Conversely, exon II and IIa IRES activity was enhanced in high-expressing cells.

Additional assays suggest these IRESes are differentially regulated. EGF induction results in enhanced expression of Aurora A protein and upregulated IRES activity of exon II containing leaders in high-expressing cells. I propose enhanced signal transduction through the MAPK/ERK/AKT/mTOR pathway contributes to aberrant IRES activity of exon II containing 5’leaders resulting in enhanced Aurora A protein expression leading to immortalization and carcinogenesis.

The form and content of this abstract are approved. I recommend its publication.

Approved: Leslie A. Krushel

To my incredibly supportive family who never failed to believe that I would accomplish

my goal, especially during those times when I wasn’t so sure myself.

TABLE OF CONTENTS

CHAPTER

I. INTRODUCTION...... 1

Protein Synthesis…………………………………………………………….…………1

Initiation codon selection: there is more to it than just scanning……...………… 5

Regulation of cap-dependent translation initiation………..…………………….10

Internal initiation of translation: viral IRESes………….……………………….14

Internal initiation of translation: cellular IRESes……..………………………...19

Regulating IRES activity: cis-elements…...……………………………………..20

Regulating IRES activity: IRES trans-acting factors……………..……………..23

Regulating IRES activity: signaling pathways………...………………..……….25

IRESes and disease……………………………………………………………....29

Fragile X Syndrome………………………………………………………………..…31

Molecular mechanisms of FXS………..…………………………………………32

Physiological functions of FMRP……………………………………………..…32

The mGluR theory and The GABAAR theory…………………..……………….36

The pre-mutation allele…………………………………………………………..40

Molecular mechanisms of the pre-mutation allele…….…………………………41

Questions………………….………………….………………………………….44

Defining Cancer: A History of Theories from Ancient to Modern Times……...……44

The Humoral Theory ……………..……………..………………………………45

The foundation for scientific oncology: a pathological approach ………………46

Theories from the 18th and 19th centuries ………………….……………………48

The modern definition of cancer………………………...…………………….…49

Molecular Mechanisms of Cancer Development……………………….…………….51

The Central Dogma and cancer research: a small overview……………………..51

DNA processes: genetic mutations……………………………...……………….53

DNA processes: epigenetics…………………………………..…………………58

Aberrant transcription……………………………………………………………59

The loss of translational control ………………………….……………………..64

The Aurora A Oncoprotein……………...……………………………………………70

Aurora A kinase and the cell cycle………………………………..……………..71

Aurora A function………………...……………………………………………...73

The Aurora A oncogenic signaling pathway…………………………………….76

Targeting Aurora A in cancer cells …………………..………………………….83

Questions: overview of study…………….………………………………………85

II. MATERIAL AND METHODS..……………………………………………………..87

Constructs and Cloning……….………………………………………………………87

In vitro Transcription…………………...………………………………………….…89

In vitro Translation……………………………….…………………………………..89

Cell Culture Maintenance…………………………………………………………….90

DNA and RNA Luciferase Assays…………………..……………………………….90

Simulated Neuronal Activity Treatments………………….…………………………91

Cap-dependent Inhibition Assays…………………………………………………….91

Western Blot Analysis…..……………………………………………………………92

Polysome Analysis……………………………………………………………………94

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RNA Extraction/qRT-PCR……………………………...……………………………94

siRNA Human Kinase Phosphotase Library Screen………………………………….94

EGF Induction…..………………………………………………………………….…96

Human Phospho-Kinase Proteome Array……………………………………….……97

III. REGULATION OF THE FMR1 IRES IN NEURONAL-LIKE CELL LINES……100

Introduction………………………………………………………………………….100

Results………..……………………………………………………………………...102

The FMR1 5’ leader directs expression of the second cistron in a dicistronic construct………………………………………………………………………...102

The FMR1 5’ leader contains a cryptic promote………………………….……103

The FMR1 5’ leaders exhibits IRES activity from a dicistronic RNA…………105

Translation of a moncistronic mRNA in vitro and ex vivo indicates a key role for IRES-dependent translation mediated by the FMR1 5’ leader.…………….108

Endogenous FMRP expression is unaffected by reducing cap-dependent translation……………………………………………………………………….109

Multiple regions in the 5’ leader contribute to FMR1 IRES activity.…….……112

Changes in intracellular pH regulate the FMR1 IRES……………………….…112

The CGG repeats contribute to FMR1 IRES activity…..………………………114

FMR1 IRES activity is affected by multiple cellular stimuli..…………………114

Discussion…………………………………….……………………………………..117

Summary of findings………………………..…………………………………..117

Cryptic promoters require the use of RNA reporter constructs………………...120

The evolutionarily conserved CGG repeats can upregulate translation of the FMR1 mRNA……………………………………………………………121

Characterization of the FMR1 5’ leader……………………………..…………122

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IRES activity contributes to the regulation of FMRP synthesis during multiple neuronal events………………..………………………………………122

IV. IRES-DEPENDENT TRANSLATION IS THE PRIMARY MECHANISM CONTRIBUTING TO AURORA A OVER- EXPRESSION IN A SUBSET OF EPITHELIAL CELL LINES……………………………………………………….124

Introduction………………….………………………………………………………124

Results……………………………….………………………………………………126

Enhanced protein synthesis contributes to over-expression of the Aurora A Kinase…………………………………………………………126

Cap-dependent translation initiation is increased in the immortalized cell lines………………………………………………………………………...133

Aurora A protein expression level is unaffected by inhibiting cap-dependent translation initiation…………...………………………………………………..138

The Aurora A 5’ leader contains an IRES..……………………………….……140

Aurora A IRES activity is increased in the cell lines that over-express Aurora A protein…………………………..……………………………………144

Further correlation between Aurora A IRES activity and protein expression………………………………………………………………………149

Discussion…………………………….…………………………………………..…153

Determining the potential “IRES Usage” of the Aurora A 5’ leader…………..154

A novel target for repressing Aurora A protein expression in cancer…………156

V. TRANSLATIONAL REGULATION OF AURORA A KINASE EXPRESSION IN CANCER………………………………………………………………………...159

Introduction……………………...…………………………………………………..159

Results……………...………………………………………………………………..163

Identification of nine alternatively spliced 5’ leader if the Aurora A mRNA….163

Three independent IRES elements reside in exons Ib, II, and IIa of the 5’ leader of the Aurora A gene…………………………..………………164

Six Aurora A variants can initiate translation cap-independently…………...…169

Exon II and exon IIa transcripts are associated with high molecular weight polysomes in MCF12A cells………………………….…………………...……172

PKM2 is identified as a potential ITAF for the Aurora A 5’ leader in HeLa cells……………………………………………………………...... 174

The ERK signaling pathway may regulate IRES-dependent translation of the Aurora A 5’ leader in HeLa cells…………………….…………………………176

MEK inhibitors decrease Aurora A protein expression in HeLa cells…..……...178

EGF induces increased Aurora A protein expression…………………………..180

Proteome array of the four breast lines…………………………………………182

EGF induces increased activity of the exon II IRES in MCF12A cells………...185

Exon II containing Aurora A transcripts are associated with HMW polysomes in response to EGF induction of MCF12A cells……………………………..…186

Discussion….………………………….…………………………………………….190

Why are there multiple 5’ leaders all of which contain the same ORF?...... 191

Multiple mechanisms may contribute to over-expression of Aurora A protein..192

Signaling pathways and Aurora A IRES activity………………………………194

VI. CONCLUSIONS AND FUTURE DIRECTIONS…………………………………197

Why Study Translation Initiation of Cellular Messages?…...………………………197

Why Study IRES-dependent Translation Initiation?...... …………………..…..199

But Do Cellular IRESes Even Exist?...... ………..201

What Were Once Vices Are Now Habits: The History of IRES Assays…………....204

The 5’ Leader of the FMR1 mRNA Contains a Real IRES…………………………208

The FMR1 IRES: Future Directions………………………………………………...209

Understanding the Physiological Role of the FMR1 IRES in Neuronal Dendrites…213

Is Targeting Aurora A Kinase Activity a Good Idea for Cancer Treatment?……….215

An Argument for Studying Activity of the Aurora A IRESes………………………216

The Aurora A IRESes: Future Directions and Final Thoughts……………………...218

REFERENCES…………………………………………………………………………227

APPENDIX

A. Primer Sets…………………………………………………………………………..264

B. Polysome Gradients………………………………………………………………….265

C. siRNA Human Kinase/Phosphatase Library Screen………………………………...266

D. Human Phospho-Kinase Array……………………………………………………...292

LIST OF TABLES

Table

1.1 Cellular mRNAs with Internal Ribosomal Entry Sites……………………..…….21

1.2 The physical and behavioral effects of the CGG trinucleotide repeat expansion of the FMR1 gene on the X chromosome……………………………………...…33

2.1 Primary and secondary antibodies………………………………………………..93

2.2 Reverse transfection with INTERFER-in………………………….……………..95

2.3 RNA transfection with TransMessenger………………………………………….96

xii

LIST OF FIGURES

Figure

1.1 A schematic representation of cap-dependent translation initiation…………...….2

1.2 Formation of the first peptide bond………………………………………………..4

1.3 Regulation of cap-dependent translation initiation by the 4E binding proteins…..13

1.4 Classification of viral IRESes…………………………………………………….17

1.5 Schematic representation of interacting pathways that regulate protein synthesis………………………………….……………………………………….27

1.6 Fragile X mental retardation protein (FMRP) function in neurons………………35

1.7 The Excitatory/Inhibitory (E/I) imbalance of FXS……………………………….38

1.8 The relation between CGG repeats in the pre-mutation range and possible effects for the pre-mutation carrier…………………………..…………42

1.9 Repair pathways of DNA double-stranded breaks………………………………..56

1.10 Aurora A expression, location and function during the cell cycle...…………….72

3.1 The FMR1 5' leader exhibits putative IRES activity, but also contains a cryptic promoter……………………………………………………………….104

3.2 Ex vivo and in vitro studies demonstrate IRES activity mediated by the FMR1 5' leader…………………………………………………………...106

3.3 FMRP expression is maintained when cap-dependent translation is reduced by rapamycin or eIF4E siRNA………………...…………………………………..110

3.4 Truncations and ameloride treatment identify regions in the FMR1 5' leader important for IRES activity.………………….………………………..113

3.5 Exposure to KCl alters FMR1 IRES activity and FMRP expression……….…..115

3.6 Exposure to poly I:C alters FMR1 IRES activity……………………………….118

4.1 Post-transcriptional regulation contributes to enhanced expression of the Aurora A protein in subset of immortalized cell lines…...... 128

xiii

4.2 G2/M populations of asynchronous cells do not correlate with Aurora A protein levels………………………………………………………….130

4.3 Aurora A protein stability is similar in the set of cell lines……………………..132

4.4 Aurora A transcripts are associated more with the HMW polysome in MCF12A cells compared to MCF-7 cells…………………….………………134

4.5 Changes in cap-dependent translation initiation do not correlate with Aurora A protein expression levels……………..…………………………….…136

4.6 Inhibiting cap-dependent translation initiation does not affect Aurora A protein expression…….………………………………………………139

4.7 The 5’ leader of the Aurora A mRNA contains an IRES………………….....…142

4.8 Aurora A IRES activity is increased in the subset of immortalized cell lines..…145

4.9 Translation initiation of the Aurora A 5’ leader of an ApppG capped transcript is enhanced in Aurora A over-expressing cells…………..…………..147

4.10 Additional cell lines over-expression Aurora A protein…………………...…..150

4.11 Protein stability is similar between the additional lines and low Aurora A expressing cells………………………………..………………..151

4.12 Additional breast epithelial cell lines demonstrate a correlation between Aurora A IRES activity and Aurora A protein expression…………….………152

5.1 Schematic diagram of the 5’ UTR of the Aurora A Gene and the alternate splicing variants of the 5’ leader of the Aurora A mRNA………...165

5.2 Schematic representation of the ApppG capped single luciferase assay………..167

5.3 Exons Ib, II and IIa contain IRES elements………………………………..……168

5.4 Four leaders contain IRESes that are more active in the Aurora A over-expressing cell lines…………………..……………………………………170

5.5 Exon II and exon IIa transcripts are associated more with the HMW polysome in MCF12A cells compared to MCF-7 cells……………...173

5.6 PKM2 is a potential ITAF for the Aurora A 5’ leader IRES…………………....175

5.7 siRNA human kinase/phosphatase library screen……….………………………177

xiv

5.8 MEK inhibitors in HeLa cells………………………………………………….179

5.9 EGF induction increases Aurora A protein expression and decreases Aurora A mRNA levels in MCF12A cells…………………...………………….181

5.10 EGF induction in MCF12A cells affect AKT and mTOR signaling………..…183

5.11 Phosphorylation states of ERK, AKT and mTOR residues under normal growth conditions…………………………………………………...…184

5.12 EGF induces activity of the exon II IRES in MCF12A cells……………..……185

5.13 Exon II transcript association with the HMW polysome in MCF12A cells increases in response to EGF induction…………..……………………………188

6.1 Proposed model for translational regulation of the Aurora A kinase...... 219

6.2 Future directions for signaling pathways………………………………………..222

CHAPTER I

INTRODUCTION

Protein Synthesis

Protein synthesis is the translation of genetic information from a nucleic acid

template (messenger RNA or mRNA) into an amino acid sequence (protein). Each

nucleic acid template contains a specific variation of the 61 codons that code for the 20

amino acids needed to make all cellular proteins. The template also contains at least one of the three stop codons to terminate translation. Eukaryotic mRNA is typically comprised of a 5’ end 7-methyl-guanisine (m7G) cap structure, the 5’ untranslated region

(UTR), a coding sequence or open reading frame (ORF), a 3’ UTR and a polyadenylic acid or poly (A) tail. Other major components of translation include ribosomal RNA

(rRNA), transfer RNA (tRNA) and various proteins or factors that make up the translation machinery such as the ribosome. The 80S ribosome is comprised of the 60S and 40S ribosomal subunits. The 60S subunit is made up of a total of fifty proteins along with the 28S, 5.8S and 5S rRNAs. The 40S subunit is comprised of thirty three proteins and the 18S rRNA (Klein and Ochoa 1972; Morgan, Menetret et al. 2000). Together these components control the three steps of translation: initiation, elongation and termination.

Initiation begins with the recruitment of the initiation machinery to the 5’ UTR of the mRNA (Figure 1.1). First, the cap structure is recognized by eukaryotic initiation factor 4E (eIF4E). This step is followed by the recruitment of eIF4G (a scaffolding protein) and eIF4A (a helicase) to form the eIF4F complex (Sonenberg 1988; Haghighat and Sonenberg 1997; Ptushkina, von der Haar et al. 1998). By interacting with eIF4G,

Figure 1.1: A schematic representation of cap-dependent translation initiation Recognition of the m7G cap structure of the 5’ UTR of a eukaryotic mRNA by eIF4E is the main regulatory step of cap-dependent translation initiation. eIF4E along with eIF4G and eIF4A form the eIF4F complex. Recruitment of additional factors completes the formation of the preinitiation complex. They include eIF4B, eIF3, the 40S ribosomal subunit and the ternary complex (eIF2, the initiator tRNA and GTP -orange triangle). According to the scanning hypothesis (Kozak 1978; Kozak and Shatkin 1978), this complex scans the 5’ leader until it reaches the initiation codon where the 40S joins the 60S ribosomal subunit to form the 80S ribosome.

eIF3 brings the 43S pre-initiation complex (PIC) to the 5’UTR. The PIC is comprised of

the 40S ribosomal subunit, eIF4B (another helicase), and the ternary complex (Benne and

Hershey 1978; Peterson, Merrick et al. 1979). Formation of the ternary complex (eIF2,

Met . GTP and a tRNA carrying methionine or Met-tRNAi ) requires recycling of eIF2 GDP

to eIF2.GTP by the guanine exchange factor, eIF2B (Nika, Yang et al. 2000; Williams,

Price et al. 2001).

In addition to eIF3, eIF5 helps recruit the 43S PIC to the mRNA, facilitated by

eIF1 and eIF1A, to form the 48S PIC (Trachsel, Erni et al. 1977; Benne and Hershey

1978; Majumdar, Bandyopadhyay et al. 2003). Helicase activity from eIF4A assisted by eIF4B unwinds any RNA structure so that the PIC can scan the 5’ UTR until it locates the initiator codon of the ORF (Kozak 1978; Kozak and Shatkin 1978). eIF5 facilitates hydrolysis of eIF2 bound GTP during recognition of the initiation codon (Yamamoto,

Singh et al. 2005). Release of the factors from the PIC and the joining of the 60S ribosomal subunit requires hydrolysis of GTP brought in bound to eIF5B and catalyzed by eIF6 (Pestova and Kolupaeva 2002). The 60S and 40S ribosomal subunits forms the

80S ribosome and translation of the mRNA template begins (Stoneley and Willis 2004).

Elongation begins with the formation of the initial peptide bond (reviewed in

(Merrick 1992).The 80S ribosome contains an E site, P site and A site (Figure 1.2). The

E site is the exit site, the P site is the peptidyl-tRNA site, and the A site is the site for the binding of incoming aminoacyl-tRNAs (Rheinberger, Sternbach et al. 1981; Rodnina,

El'skaya et al. 1988; Triana, Nierhaus et al. 1994; Agrawal, Penczek et al. 1996). The

start codon, usually an AUG, is positioned at the P site and the next codon at the A site.

Met An aminoacyl-tRNA (aatRNA) carrying methionine, Met-tRNAi , attaches to the start

A E

b D

Figure 1.2 Formation of the first peptide bond Recognition of the start codon (AUG) by the 40S ribosomal subunit signals formation of the 80S ribosome with the initiator tRNA firmly entrenched in the P site (not shown). (A) An aminoacyl- tRNA able to base pair with the next codon on the mRNA arrives at the A site associated with an elongation factor EF-1 and GTP. (B) GTP hydrolyzes and the aminoacyl-tRNA is placed in the A site. (C) The preceding amino acid (Met at the start of translation) is covalently linked to the incoming amino acid with a peptide bond and is transferred from the P-site tRNA to the A-site tRNA. Immediately following peptidyl transfer, the ribosome fluctuates between the classic state and a hybrid state. (D) EF-2•GTP favors binding to the hybrid state and hydrolyzes GTP to irreversibly commit the ribosome to translocate (not shown). Once the ribosome has moved down the mRNA one codon, it returns to the classic state with a deacylated tRNA in the E site, a peptidyl-tRNA in the P site and an open A site. (E) Simultaneously with A-site accommodation, the deacylated tRNA is removed.

codon via an anti-codon at the P site. Next, a tRNA carrying the amino acid encoded by

the second codon attaches at the A site. A peptide bond is formed between the two amino

acids and elongation begins (Sachs 1997). The ribosome then shifts one codon so that the

first tRNA, now deacylated, is in the E site, the second pepidyl-tRNA (pep-tRNA)

connected to the growing polypeptide chain is at the P site and the A site is empty

allowing for the attachment of the next tRNA (Figure 1.2).

This process requires a lot of energy. The formation of each peptide bond costs a

total of 4 high energy bonds. To make the pep-tRNA, two high energy bonds are used

converting ATP to AMP. Elongation factor -1α (EF1-α) along with a guanine exchange

factor EF-1β recruits the aatRNA to the A-site via GTP hydrolysis. The final energy bond

is acquired by hydrolysis of a second GTP associated with EF-2 to translocate the aatRNA from the A site to the P site (Ryazanov, Rudkin et al. 1991). Elongation continues until a stop codon (UAA, UAG, UGA) is placed in the A site signaling termination.

Translation termination requires two release factors (RF) and one high energy bond. The release factor eRF1 recognizes the termination codon ending protein synthesis. eRF3 is a ribosome-dependent GTPase that helps eRF1 release the completed polypeptide (Salas-Marco and Bedwell 2004; Pisareva, Pisarev et al. 2006). The two

ribosomal subunits separate from the mRNA, the translation machinery dissociates and

the newly formed protein is released for further processing.

Initiation codon selection: there is more to it than just scanning

After the 40S ribosomal subunit is recruited to a message it must identify the

correct start codon to translate the encoded protein. Above, I introduced the most well

5 known mechanism of translation initiation used in eukaryotes, the cap-dependent scanning hypothesis. This hypothesis postulates that after the PIC is recruited to the mRNA it will scan the length of the 5’ UTR until it encounters an initiation codon that is in “good context”. An initiation codon in good context is called the Kozak sequence

(Kozak 1978). The AUG in a Kozak sequence is one flanked by a purine at the -3 and +4 positions. Guanines are preferred but adenines will work at the -3 position as well

(Cavener 1987; Kozak 1987).

The classic scanning mechanism has been shown to require a 5’ m7G cap for ribosomal recruitment. However, there are many conditions that are not conducive to a scanning mechanism. The longer the 5’UTR the higher the probability is that the ribosome will dissociate from the message prior to reaching the start codon, suggesting scanning may be a very inefficient process. ATP hydrolysis is also thought to be required

(Kozak 1980) thereby scanning a long 5’ UTR would be costly in terms of cellular energy. Any upstream ORFs (uORFs) and/or secondary structure of the RNA appear to obstruct the scanning ribosome (Kozak and Shatkin 1978; Kozak 1979; Pelletier and

Sonenberg 1985; Kozak 1986; Mueller and Hinnebusch 1986; Cigan, Pabich et al. 1988).

[A quick aside –the presence of uORFs indicates that not all 5’ UTRs are untranslated, therefore I will often refer to them as 5’ leaders instead.] Indeed, stable hairpin structures with a free energy of greater than -50 to -60kcal/mol will inhibit cap-dependent translation (Pelletier and Sonenberg 1985; Kozak 1986) but evidence that this is the result of blocked ribosomal scanning is indirect. This data could result from the hairpin structure inhibiting recruitment of the translation machinery to the message. That being said, the processivity of the ribosome was shown to remain intact on lengthy 5’ UTRs but

only if unstructured and not containing uORFs (Berthelot, Muldoon et al. 2004). Also,

scanning of an unstructured 5’ UTR has been shown to occur without the requirement of

ATP (Kozak 1980; Kozak 1980; Pestova and Kolupaeva 2002). Taken together these two

studies suggest it would not require a great deal of energy for the ribosome to scan a long

leader but only in the absence of any deterrents.

Ribosomal scanning is widely accepted but like most biological mechanisms there

are exceptions to the rule. Messages with uORFs are still translated. In situations like this

one the ribosome is said to bypass start codons that are close to the 5’ end in preference

for one further downstream by a mechanism called leaky scanning (Kozak 1987). Re-

initiation is another mechanism proposed to overcome the obstacle of an uORF, as long

as it contains a stop codon prior to the ORF to allow for termination of the first mini

transcript (Kozak 1987).

However, there are additional exceptions that cannot be explained by these

alternate mechanisms. A subset of mRNA contains start codons that are not in a good

Kozak sequence context (Mueller and Hinnebusch 1986; Mihailovich, Thermann et al.

2007). Non-AUG codons such as CUG and AUA have been observed to be utilized as

initiation codons by a few eukaryotic mRNAs in Drosophila and C. elegans (Touriol,

Bornes et al. 2003). And how are long highly structured 5’ UTR containing transcripts

translated? Clearly, these exceptions suggest something other than recognition of a good

Kozak context can assist the ribsome with finding the correct initiator codon.

Lengthy leaders with extensive secondary structure have been shown to impede the ribosome from reaching the start codon (Pelletier and Sonenberg 1985; Kozak 1986;

Babendure, Babendure et al. 2006; Abaeva, Marintchev et al. 2011). Ribosomal shunting

has been proposed to bypass these structures. This mechanism was first observed on the

cauliflower mosaic virus. The ribosome utilizes cis-acting sequences as acceptor and donor sites that flank the structure allowing for the ribosome to jump or shunt around it

(Fütterer, Kiss-László et al. 1993). Some eukaryotic mRNAs that contain short complementary sequences to ribosomal 18S RNA can facilitate shunting around structures that block scanning such as in frame upstream AUGs or hairpins (Yueh and

Schneider 2000; Chappell, Dresios et al. 2006). For example, the 5’ UTR of the GTX gene includes a 9 nt segment that is complementary to 18S rRNA. Compensatory mutations of the leader sequence and the 18S rRNA demonstrated that the complementary sequence is able to bind the 40S ribosome and facilitate initiation of translation similar to the prokaryotic Shine-Dalgarno sequence (Chappell, Edelman et al.

2000; Chappell, Dresios et al. 2006).

There are two additional cap-dependent mechanisms that do not involve scanning at all. Ribosomal tethering proposes the 40S ribosomal subunit is fixed to the mRNA at

Met the 5’ end and through association with the Met-tRNAi , it manages to find the

initiation codon by simply looping out past the intervening sequence (Chappell, Edelman

et al. 2006). Ribosomal clustering does not require the 40S subunit to remain associated

with the 5’ end but instead suggests that it is able to reversibly bind to upstream or

downstream AUGs until it finds the correct initiation codon to begin translation. This

mechanism is also referred to as ribosomal jumping (Chappell, Edelman et al. 2006). A

major problem with these ideas is there is no explanation as to how proper orientation of

the 40S subunit is maintained so that it lands perfectly on the start codon. I would predict

the presence of some sort of regulatory element would be required, for instance

something similar to a Shine-Dalgarno sequence or a conserved structure like those

observed in viral 5’ UTRs.

And finally, there is a cap-independent mechanism to initiate translation on long

structured 5’UTRs that may or may not contain uORFs. An Internal Ribosomal Entry

Site (IRES) can be used to recruit the ribosome internally therefore bypassing the

recognition of the cap structure by eIF4E. Initially identified in picornaviruses, IRESes

have been found in eukaryotic messages as well. Regardless of the differences between

cap and IRES–dependent ribosomal recruitment, once associated with the mRNA,

initiation codon selection is still determined by scanning, leaky scanning, reinitiation,

shunting, clustering and even an IRES version of tethering (Jang and Wimmer 1990;

Belsham 2000; Jan and Sarnow 2002; Jopling, Spriggs et al. 2004; Chappell, Edelman et al. 2006; Shatsky, Dmitriev et al. 2010).

Like many scientific ideas, the main criticism of the scanning hypothesis is the

lack of direct evidence. A new high-throughput technique may finally provide the

answers needed to put the conflict to rest. With this experiment the position of a

translating ribosome can be determined by combining ribosomal footprint assays with

deep sequencing (Ingolia, Ghaemmaghami et al. 2009). The possibility of capturing the

movement of the ribosome from the 5’ end to the 3’ end of a message is exciting.

However, due to the multiplicity of mechanisms that have been suggested to initiate

translation, I would predict that along with disputing some of these ideas this assay will

reveal even more possibilities.

Regulation of cap-dependent translation initiation

Protein synthesis can be regulated during initiation, elongation or termination but

the complexity of each step is proportional to the amount of regulation that occurs

(Groppo and Richter 2009). Therefore, the major regulatory step in translation of eukaryotic mRNA is initiation. Indeed, it is energy efficient to determine if a message needs to be translated prior to the high energy cost of the elongation process. The 3’UTR of mRNA also plays an important role in translation initiation. Communication between the 5’ and 3’ end of mRNA occurs when eIF4E bound to the 5’ cap structure and poly

(A) binding protein (PABP) bound to the 3’ poly (A) tail jointly interacts with eIF4G resulting in circularization of the mRNA. This conformation increases the stability of the translation initiation machinery as well as mRNA stability resulting in increased translation (Wells, Hillner et al. 1998).

There are two PABP regulatory proteins, PABP-interacting protein 1 (Paip1) and

Paip2 that compete through binding events with PABP. Paip1 has 25% identity and 39%

similarity with the central domain of human eIF4G (aa 420 to 890) which contains one of

the two known eIF4A binding sites (Imataka and Sonenberg 1997). Consequently, Paip1

interacts with eIF4A and was shown to stimulate translation of a reporter mRNA in

cultured mammalian cells (Craig, Haghighat et al. 1998). On the other hand, the highly

acidic Paip2 represses translation in vitro and in transfected cells (Khaleghpour, Svitkin

et al. 2001). In addition to competing with PaiP1 for binding to PABP, Paip2 inhibits

binding of PABP to the poly(A) tail to further downregulate protein synthesis

(Khaleghpour, Svitkin et al. 2001).

Additional proteins can inhibit cap-dependent translation initiation by interacting

with both the 3’ and 5’ends of a transcript. For instance, during oocyte maturation and

early embryonic divisions DNA is not transcribed. Instead these cells contain maternal

mRNAs that need to be regulated so that they can be translated at the appropriate times.

Cytoplasmically polyadenylated maternal mRNA contains cytoplasmic polyadenylation

elements (CPE) in their 3’UTRs. The cytoplasmic polyadenylation element binding

protein (CPEB) binds CPEs to both promote translation by stimulating elongation of the

poly (A) tail and repress translation by recruiting maskin. Maskin contains an eIF4E

binding site that is thought to compete with eIF4G. It also binds directly to CPEB. The

resulting circularization of the mRNA prevents recruitment of the preinitiation complex

thereby inhibiting translation. Circularization resulting from these 3’ and 5’ interactions

also protect mRNA integrity by limiting access of other regulators that target the 3’UTR.

MicroRNAs (miRNA) play a role in mRNA stability and protein synthesis via 3’

UTR interactions. These short RNA sequences, typically 22 nt long, bind complementary

sequences in the 3’ UTR of multiple target mRNAs, usually resulting in their silencing.

The miRNA shuttles target messages to cytoplasmic P-bodies for degradation or

translational repression (Liu, Valencia-Sanchez et al. 2005). This association with P-

bodies suggests miRNA is also involved in ARE-mediated mRNA turnover.

AREs are AU-rich elements, also within the 3’ UTR, that interact with different

ARE binding proteins (ARE-BPs). The well studied ARE-BP, tristetraprolin (TTP), can

assist shuttling target RNAs to P-bodies for degradation or translational repression

(Kedersha, Stoecklin et al. 2005). Additionally, TTP can directly recruit decapping

enzymes or the exosome to the target RNA and destabilize it (Gherzi, Lee et al. 2004;

Fenger-Gron, Fillman et al. 2005).

Cellular stimuli via growth factor and/or hormone signaling can also regulate cap-

dependent translation (Pyronnet, Dostie et al. 2001). For example, the

phosphatidylinositol-3/AKT/ mammalian target of rapamycin (PI3/AKT/mTOR)

signaling pathway regulates cap-dependent translation via the interaction of eIF4E with its negative regulators, the 4E binding proteins (4E-BPs) (Gingras, Gygi et al. 1999).

Phosphorylation of 4E-BP1 mediated by the mTOR kinase decreases the binding affinity

of 4E-BP1 to eIF4E thereby enhancing cap-dependent translation initiation. In a

hypophosphorylated state, 4E-BP binds and sequesters eIF4E. This interaction limits

access of eIF4E to the cap structure, prevents 4E/4G binding and inhibits cap-dependent

translation (Richter and Sonenberg 2005). Drugs that inhibit mTOR kinase activity, such

as rapamycin, lead to increased levels of hypophosphorylated 4E-BP resulting in

decreased access of eIF4E to the cap structure and reduced cap-dependent translation

(Sawyers 2003) (Figure 1.3).

There are cellular stressors such as such as apoptosis, and hypoxia that inhibit

cap-dependent translation initiation (Pyronnet, Dostie et al. 2001). The interaction

between eIF2 and its guanine nucleotide exchange factor eIF2B are controlled in

response to such stressors (Harding, Zhang et al. 1999). Phosphorylation of the eIF2α

subunit increases the affinity of eIF2 for eIF2B. This interaction prevents nucleotide

exchange of GDP, limiting ternary complex formation and inhibiting protein synthesis

(Pavitt, Ramaiah et al. 1998).

Figure 1.3: Regulation of cap-dependent translation initiation by the 4E binding proteins The sequestering of eIF4E by hypophosphorylated 4E-BP1 inhibits the formation of the required eIF4F complex (eIF4E, 4G, and 4A) and downregulates cap- dependent translation initiation of eukaryotic mRNAs. Cap-dependent translation initiation is upregulated in response to activation of the PI3/AKT/mTOR pathway, resulting in hyperphosphorylated 4E-BP1. In this state 4E-BP1 can no longer interact with eIF4E, allowing formation of the eIF4F complex. Inhibition of the PI3/AKT/mTOR pathway through the use of drugs such as rapamycin will also inhibit cap-dependent translation initiation due to a decrease of hyperphosphorylated 4E-BP1.

Finally, there are times during normal cellular processes, such as mitosis, when protein synthesis is thought to be downregulated. Prior to the G2/M phase of the cell cycle the amount of protein in the cell has to double. This processes requires an enormous amount of energy (Pardee 1989). Therefore, downregulation of protein synthesis would not deplete the cell of energy required for mitosis. Indeed, cap-dependent translation is inhibited during G2/M by decreased PI3/AKT/mTOR signaling resulting in increased hypophosphorylated 4E-BPs (Pyronnet and Sonenberg 2001). However, ongoing synthesis of essential proteins during G2/M (or apoptosis or hypoxia) is still needed.

Fortunately, there is an alternate mechanism to initiate translation that is utilized by many of the mRNAs encoding these essential proteins.

Internal initiation of translation: viral IRESes

As previously mentioned, an alternative mechanism utilized by eukaryotes to initiate translation involves the binding of the translation preinitiation complex in conjunction with non-canonical RNA-binding proteins to sites on the 5’ leader termed

Internal Ribosomal Entry Sites (IRESes), irrespective of the presence of a cap structure

(Jang, Krausslich et al. 1988; Pelletier and Sonenberg 1988; Jang, Davies et al. 1989).

This cap-independent mechanism was first identified and best characterized in viruses.

Viral RNAs need to compete with host RNA for the cells translational machinery, therefore viral mechanisms that inhibit host cell protein synthesis while maintaining translation of viral RNAs evolved. For this reason, viruses were used in early studies of translational mechanisms of mammalian cells. Scientists were perplexed why the 5’UTRs of these viruses, which possess characteristics that aren’t conducive to the classic

14 scanning mechanism of cap-dependent translation initiation, could be efficiently translated.

These 5’ untranslated regions are long, 600-1200 nucleotides, an extensive secondary structure originally thought to be due to a prevalence of guanine and cytosine nucleotides (Pilipenko, Blinov et al. 1989; Belsham 2000). Additionally, these UTRs often contain multiple initiator codons resulting in upstream open reading frames (uORF)

(Jackson and Kaminski 1995; Vagner, Galy et al. 2001). The poliovirus RNA was shown to possess a 5’ terminal pU residue instead of a cap structure (Nomoto, Lee et al. 1976) so it was argued that perhaps these viruses utilized a cap-independent mechanism to initiate translation . To test this hypothesis the 5’UTR of the polio virus and another member of the Picornviridae family, the encephlomyocarditis virus (EMCV), were place inbetween two cistrons on a single dicistronic transcript. It was determined both UTRs could internally initiate translation of the downstream cistron via what was termed an

IRES element (Jang, Krausslich et al. 1988; Pelletier and Sonenberg 1988). This result was supported when circular RNAs containing the EMCV 5’UTR were shown to be translated by ribosomes while RNAs lacking an IRES element were not (Chen and

Sarnow 1995).

The structure of viral IRESes appears to be highly conserved among related viruses allowing for the IRESes to be phylogenetically classified. For example,

Picornaviridae IRESes have been divided into three groups based on structure. Type I viruses include the enteroviruses and rhinoviruses. Type II viruses consist of cardioviruses, aphthoviruses, and parechoviruses. The third type is a minor group containing hepatitis A virus (HAV) (Jackson, Howell et al. 1990). Structural similarity is

seen among other viral IRESes too, including human immunodeficiency virus (HIV),

hepatitis C virus (HCV) and HCV-like IRESes (Honda, Beard et al. 1999; Easton, Locker et al. 2009; Weill, James et al.).

Mutational analysis of viral IRESes demonstrates the importance of secondary

structure. For example, mutations that affect the secondary structure of the base of a

specific stem loop in the foot and mouth disease virus (FMDV) IRES dramatically

decreases internal initiation by interfering with eIF4G binding (Martinez-Salas, Lopez de

Quinto et al. 2002). eIF4G also binds to a similar RNA structure in the

encephalomyocarditis virus (EMCV) IRES suggesting that the secondary structures are

conserved to maintain IRES function (Kolupaeva, Pestova et al. 1998). Interestingly,

sequence variation exists between virus families yet overall structure is preserved due to

covariant substitutions. This evolutionary conservation further emphasizes the

importance of these structural elements to viral IRES function.

Viral IRESes can also be classified based on canonical factor requirements

(Figure 1.4) (Filbin and Kieft 2009). The Picornaviridae IRESes require eIF4G, eIF4A,

eIF4B, eIF3, eIF2 and some non-canonical factors (Pestova, Maslova et al. 1989;

Pilipenko, Pestova et al. 2000; Borman, Michel et al. 2001). The EMCV IRES requires

eIF4A and eIF4G along with the non-canonical factor polypyrimidine tract binding

protein (PTB) to recruit the 40S ribosomal subunit (Borovjagin, Pestova et al. 1994;

Lomakin, Hellen et al. 2000). Some viral IRESes require only a subset of eIFs and the

40S ribosomal subunit. This group includes the HCV IRES that requires eIF3 to initiate

translation. Other members of this group are the classic swine fever virus IRES and

Figure 1.4

Group 4 IRES: Polio, HAV IRES

IRES

Group 2 IRES: ORF HCV IRES J

Group 1 I RES: ORF 1CrPV IRES

Figure 1.4 Classifications of viral IRESes Viral IRESs can be separated into four different classes based on structural complexity and canonical factor requirements. Group 1: This class of viral IRESes is the most structurally compact and members are able to facilitate ribosomal recruitment with no initiation factors at all. Additionally, these Met IRESes do not require Met-tRNAi . Group 2: The second class of viral IRESes requires a minimal set of canonical initiation factors such as eIF3, eIF2, and the 40S ribosomal Met subunit as well as Met-tRNAi . Group 3: These IRESs that are not heavily compacted Met and were shown to require eIF4G, eIF4A, eIF4B, eIF3, eIF2, Met-tRNAi and some non-canonical factors. Group 4: The last group of IRESes requires some canonical eIFs, Met Met-tRNAi and non-canonical factors. Compared to the other groups this one is able to initiate at a start codon a bit downstream of the IRES (Kieft 2008).

members of the Flaviviridae family (Pestova, Shatsky et al. 1998; Kieft, Zhou et al. 2001;

Locker, Easton et al. 2007). The final class of viral IRESes is comprised of members of

the Dicistroviridae family. This family contain IRESes in the intercistronic region of

their messages that require no canonical factors for the recruitment of the 40S ribosomal

subunit (Jan and Sarnow 2002; Pfingsten, Costantino et al. 2006). These IRESes are also

the most highly structured group of viral IRESes. An example of this type of IRES is the

cricket paralysis virus (CrPV) intergenic (IGR) IRES. Its structure mimics a hybrid state

tRNA in the P site of the 40S ribosome, allowing for translocation of the ribosome to

occur without an actual peptide bond formation (Costantino, Pfingsten et al. 2008; Jang,

Lo et al. 2009).

Internal initiation of translation: cellular IRESes

The existence of cellular IRESs was first shown in 1991 (Macejak and Sarnow

1991). A cellular mRNA, encoding the immunoglobulin heavy-chain binding protein

(Bip), was efficiently translated in poliovirus-infected cells when cap-dependent

translation of host cell mRNAs was inhibited. Indeed, the 5' leader of the Bip mRNA was

able to mediate translation of the second cistron of a dicistronic mRNA during poliovirus

infection (Macejak and Sarnow 1991). It was concluded that the mechanism of

translation by internal ribosome binding utilized by viruses could also occur on

eukaryotic mRNAs (Macejak and Sarnow 1991). Following these initial experiments,

analysis of polysome associated mRNAs when protein synthesis was downregulated

during mitosis or poliovirus infection led to the estimation that 3-5% of eukaryotic mRNAs are capable of initiating translation internally. The initial prediction was that

eukaryotic IRESs would exhibit similar characteristics to viral IRESs such as length of

the 5’ UTR, relative GC richness, and dependence on structure. But it turned out to be a

little more complicated.

Most of the small subset of eukaryotic mRNAs that have been shown to contain

IRESes in their 5’ leaders are often translated during processes when cap-dependent

translation is downregulated (Jackson, Hunt et al. 1995; Jackson and Kaminski 1995;

Hellen and Sarnow 2001; Vagner, Galy et al. 2001). However there are examples of

cellular IRESes located in transcripts that are translated when cap-dependent translation

is not inhibited (Table 1.1) (Pyronnet, Pradayrol et al. 2000). Even though IRES elements

are found in these leaders, it is difficult to argue if they are even utilized since cellular

mRNA also contains a cap structure. Additionally, known cellular IRESes appear to be

much less active compared to their viral counterparts (Kozak 2005). Although these

observations initially brought challenges to the biological relevance of cellular IRESes,

additional studies support the idea that the proteins translated from cellular messages

containing IRESes are not needed in great abundance to be biologically relevant (Table

1.1) (Merrick 2004). Indeed, many of these proteins must be tightly regulated suggesting something more than the general cap-dependent regulatory mechanisms are needed. To date there is no known general mechanism to regulate internal translation initiation of eukaryotic mRNA.

Regulating IRES activity: cis-elements

The cis-elements of eukaryotic IRESes appear to be more diversified compared to their viral counterparts. Eukaryotic IRESes have been found in both long 5’ leaders that are highly G/C rich as well as in short leaders with a high A/U content (Xia and Holcik

2009), ranging in size between 9 nt to greater than 200 nt. Additionally, some eukaryotic

Table1.1 Cellular mRNAs with Internal Ribosomal Entry Sites Pro/Anti Transcription Growth Factors Signaling Apoptotic Apaf-1 c-jun FGF2 p27KIP XIAP GTX TrkB PKCδ HIAP2 Mnt IGF-2 Connexin-32 Bcl-xL NKK 6.1 5-1 Rec Pim-1 Bcl-2 c-myc VEGF p58PITSLRE c-IAP n-myc PDGF2 Notch2 Bag-1 SMAD-5 Cyr61 DAP5 p53 IGFII c-myc Pim-1 Bip MYT2 NRF G2/M Phase of G1 Phase of the Oncogenes Tumor the Cell Cycle Cell Cycle Suppressors ODC c-myc c-myc APC p58PITSLRE cyclin D n-myc p53 NAPIL1 p27KIP Pim-1 p27KIP Aβ p58PITSLRE hnRNP A/B c-jun p27KIP unr Dendritically Translation Transporters/Receptors Development Localized Factors ARC DAP5 Cat-1 RUNX1 MAP2 Notch-2 MYT2 RC3 Estrogen Receptor α Antennapedia Dendrin IFG-i and II Recepter Ultrabithorax FMR1 NRF (Stoneley, Paulin et al. 1998; van der Velden and Thomas 1999; Chappell, Edelman et al. 2000; Creancier, Morello et al. 2000; Holcik and Korneluk 2000; Holcik, Yeh et al. 2000; Chiang, Carpenter et al. 2001; Creancier, Mercier et al. 2001; Pinkstaff, Chappell et al. 2001; Gerlitz, Jagus et al. 2002; Henis-Korenblit, Shani et al. 2002; Mitchell, Spriggs et al. 2003; Pickering, Mitchell et al. 2003; Holcik 2004; Martineau, Le Bec et al. 2004; Cho, Kim et al. 2005; Cornelis, Tinton et al. 2005; Dobson, Minic et al. 2005; Lewis and Holcik 2005; Liu, Dong et al. 2005; Schepens, Tinton et al. 2005; Tinton, Schepens et al. 2005; Dobson, Kube et al. 2008)

IRESes contain uORF yet some do not. Conversely a long G/C rich 5’ leader containing uORFs does not indicate the absolute presence of an IRES. For example, the 5’leader of the beta-site amyloid precursor protein cleaving enzyme 1 (BACE 1) is long (536

21 nucleotides (nt)), highly G/C rich (77%) and has 4 uORFs but it is exclusively translated in a cap-dependent manner (Koh and Mauro 2009). Despite these differences, every cellular mRNA 5’ leader containing an IRES is thought to require the utilization of all the canonical eIFs (with the exception of eIF4E) along with some non-canonical factor(s) for internal initiation of translation (Stoneley and Willis 2004; Filbin and Kieft 2009).

However, this statement is only an assumption. The c-Src IRES does not appear require eIF2 to initiate translation (Allam and Ali 2010). This example demonstrates why biochemical studies to determine the requirements for individual cellular IRESes are needed.

Cellular IRESes may depend on sequence, structure, or a combination of both to recruit the ribosome to the message. Some leaders that can internally initiate translation contain nucleotides that are complementary to 18S ribosomal RNA. The Gtx 5’ leader

(Chappell, Edelman et al. 2000) and the Rbm3 5’ leader (Chappell and Mauro 2003) contain sequences of 9 and 22 contiguous nt, respectively, that are both complementary to 18S ribosomal RNA and required for cap-independent translation. It has been postulated that these regions can directly recruit the ribosome in a manner similar to the prokaryotic Shine-Delgarno sequence. No stable structures could be identified for these segments when the sequences were subjected to the RNA-folding algorithm in mFold

(Chappell and Mauro 2003). This suggests that the importance of structure seen with viral

IRESes may not apply to a subset of eukaryotic IRESes, and instead primary sequence may play a more significant role. On the other hand, the RNA structure exhibited by the

Apaf-1 5’ leader mediates the presentation of binding sites for ITAFs necessary for IRES function (Mitchell, Spriggs et al. 2003). A correlation between high eukaryotic IRES

activity and weak secondary structure has also been demonstrated (Xia and Holcik 2009).

Due to the diversity seen in sequence and structure of cellular IRESes, they can only be identified by functional analyses.

Regulating IRES activity: IRES trans-acting factors

Non-canonical RNA-binding proteins that regulate IRES activity are called IRES

trans-acting factors (ITAFs). ITAFs are thought to bind the 5’ leader and either alter

conformation of the mRNA or stabilize a specific IRES confirmation thus enabling

recruitment of other initiating factors. The majority of the ITAFs identified thus far are

heterogeneous nuclear ribonucleoproteins (hnRNPs) which were originally identified as

part of nuclear RNA/protein complexes functioning in pre-mRNA processing (Hellen,

Witherell et al. 1993; Blyn, Swiderek et al. 1996). Other types of ITAFs include

p97/DAP5, that shares homology with the C-terminal end of eIF4G so it is unable to bind

eIF4E but can still interact with eIF4A (Imataka, Olsen et al. 1997). DAP5 promotes

IRES-dependent translation of XIAP and HIAP2 mRNA during programmed cell death

or ER induced stress (Nevins, Harder et al. 2003; Lewis, Cerquozzi et al. 2008). La

autoantigen, another RNA binding protein, has been shown to stimulate the XIAP IRES

and associate with polio and HCV IRESs to aid in 40S subunit binding (Holcik and

Korneluk 2000; Costa-Mattioli, Svitkin et al. 2004). Neuronal localization factors

associated with RNA stability, the ELAV/Hu family, have been shown to regulate the

p27 IRES and the HIF1-α IRES (Kullmann, Gopfert et al. 2002; Galban, Kuwano et al.

2008).

In response to cellular stimuli, ITAFs may relocalize from the nucleus to the

cytoplasm to regulate IRESes by promoting or inhibiting IRES activity. For example,

PTB and PCBP shuttle from the nucleus to the cytoplasm in response to chemotoxic stress and stimulate IRES-mediated synthesis of BAG-1 (Dobbyn, Hill et al. 2008).

Conversely, in response to osmotic shock, the ITAF hnRNP-A1 relocalizes to the

cytoplasm and negatively regulates the XIAP IRES (Lewis, Veyrier et al. 2007).

Additionally, cellular IRESes are regulated by a nuclear experience, a mechanism that couples nuclear processing of mRNAs and ITAF association before the mRNA is even exported into the cytoplasm. Studies show a lack of IRES activity when the Smad5,

XIAP, and c-myc mRNAs were delivered directly to the cytoplasm (Stoneley,

Subkhankulova et al. 2000; Shiroki, Ohsawa et al. 2002; Holcik, Gordon et al. 2003;

Lewis and Holcik 2008). The lack of a nuclear history can explain the weak activity

observed when testing cellular IRESes using RNA versus DNA reporter constructs.

A well studied ITAF that is part of the hnRNP family is polypyrimidine tract-

binding protein- PTB. PTB binds the RNA sequence UCUU located within a polypyrimidine tract (Wagner and Garcia-Blanco 2001), and to regions of double stranded RNA (Mitchell, Spriggs et al. 2005). Polio virus (PV), EMCV, and HCV are examples of viral IRESes which bind PTB (Jan and Sarnow 2002). PTB also binds to numerous cellular IRESes containing PTB binding motifs including Apaf-1 (Mitchell,

Spriggs et al. 2003), BAG-1 (Pickering, Mitchell et al. 2003) and HIF1α (Schepens,

Tinton et al. 2005). The Apaf -1 IRES also requires binding of unr (upstream of N-ras)

which induces a conformational change allowing PTB to bind, leading to recruitment of

the 40S ribosomal subunit (Mitchell, Spriggs et al. 2003). Additionally, PTB binds to the

mouse neurotrophin receptor TrkB 5’ leader (Timmerman, Pfingsten et al. 2008) and in

conjunction with PCBP1 binds to the BAG-1 5’ leader (Pickering, Mitchell et al. 2003).

Conversely, PTB binding has been shown to inhibit IRES activity as seen with the viral

HCV and cellular unr IRESes (Tischendorf, Beger et al. 2004; Cornelis, Tinton et al.

2005).

Unr protein is an RNA-binding protein that first identified as a transcription factor. It regulates N-ras protein expression which regulates cell proliferation. Synthesis of unr protein is upregulated in the G2/M phase of the cell cycle via an IRES in the 5’ leader of the unr message. Unr binds 11 – 14 nt long purine rich sequences that are predominantly adenosines (Triqueneaux, Velten et al. 1999). This protein has been identified as an ITAF for the cell-cycle dependent IRES which initiates translation of p58PISTLRE kinase during G2/M (Hellen and Sarnow 2001; Tinton, Schepens et al. 2005).

Unr is an interesting example in that its expression is regulated by cap-independent

translation and the protein itself upregulates expression of other G2/M associated proteins

by cap-independent translation.

Regulating IRES activity: signaling pathways

Many of the eukaryotic initiation factors contain phosphorylation sites that control

interactions with both proteins and RNA (Traugh, Tahara et al. 1976; Duncan and

Hershey 1985; Duncan, Milburn et al. 1987). As previously mentioned, cap-dependent

translation can be upregulated by the PI3/AKT/mTOR pathway via phosphorylation of

the 4E-BPs in response to cellular signals such as growth factors (Figure 1.3) (Fadden,

Haystead et al. 1997; Heesom, Avison et al. 1998). This pathway also regulates

phosphorylation of eIF4B, eIF4G1 and eIF4E (Joshi, Cai et al. 1995; Whalen, Gingras et

al. 1996; Raught, Gingras et al. 2000; Raught, Peiretti et al. 2004; Kim, Chu et al. 2005).

Additionally, mitogen-activated protein kinases (MAPK) signaling has been implicated in

regulating cap-dependent translation via phosphorylation of eIF4E, eIF4B and 4E-BP1

(Wang, Tian et al. 2003; Ballif, Roux et al. 2005) (Figure 1.5). There are a plethora of studies that indicate these pathways contribute to the regulation of cap-dependent translation. In contrast there are few studies regarding the regulation of IRES-dependent translation by signaling pathways. To date no general signaling pathway regulating IRES- dependent translation has been identified.

There are some examples of signaling pathways regulating specific cellular

IRESes. For instance, the cyclin D1 and the c-myc IRESes have been shown to be negatively regulated by AKT activity. In addition, IRES activity from these two IRESes is enhanced following exposure to rapamycin in a p38 MAPK and RAF/MEK/ERK signaling-dependent manner (Shi, Sharma et al. 2005). Another example demonstrates that activity of the egr2-IRES is upregulated by IL-1β and p38-MAPK signaling in response to inflammatory conditions (Rubsamen, Blees et al.2012). A final example of regulation of a specific cellular IRES via signaling involves the enhanced IRES activity of Laminin B1 (LamB1) by increased cytoplasmic localization of La during epithelial to mesenchymal transition (EMT). This mechanism depends on MAPK/ERK signaling downstream of platelet-derived growth factor (PDGF) (Petz, Them et al. 2012).

Recently, more studies attempting to identify a signaling pathway that could regulate global IRES-dependent translation are underway. Although no one pathway identified thus far affects all cellular IRESes there are examples of signaling pathways regulating IRES activity of messages that encode proteins required for specific events.

Figure 1.5: Schematic representation of interacting pathways that regulate protein synthesis Growth factors (green boxes) stimulates receptor tyrosine kinases (RTKs) phosphorylation which stimulates RAS activation through a series of adaptor proteins and exchange factors. Activated RAS binds and recruits RAF to the plasma membrane. RAF activates MEK which in turn phosphorylates and activates ERK. ERK regulates cytosolic proteins (and transcription factors-not shown) that are involved in cell cycle progression and survival. MNK activated by ERK interacts with eIF4G to phosphorylate eIF4E thereby increasing stability of the eIF4F complex. ERK both inhibits TSC2 and, along with RSK, phosphorylates mTOR leading to increased cap-dependent translation. Phosphorylated mTOR can form two complexes, mTORC1(mTOR, raptor, mLST8, and PRAS 40) and mTORC2(mTOR, rictor, SIN1, mLST8, and protor). mTORC1 regulates protein synthesis via the 4E-BPs (regulates eIF4E availability) and S6K (phosphorylates S6 ribosomal protein). mTORC2 function is not well understood but it is known to phosphorylate S473 of AKT. PIK3 is also activated in response to RTKs activation to generate PIP3 (negatively regulated by tumor suppressor, phosphatase and tensin homolog (PTEN)). PIP3 activates PDK1 which can phosphorylate T308 of AKT. Phosphorylation of both S473 and T308 are required for full activation of AKT. AKT controls cell growth, survival and metabolism via its numerous key substrates. AKT also directs protein synthesis by regulating mTOR through TSC2 inhibition. Stimulatory events are indicated with arrows, inhibitory events are indicated with flat lines.

During apoptosis, the fibroblast growth factor (FGF)-2-S6 kinase 2 (S6K2) pro-survival

signaling pathway activates S6K2. S6K2 in turn phosphorylates the tumor suppressor

programmed cell death 4 (PDCD4) leading to PDCD4 degradation. PDCD4 binds the X-

linked inhibitor of apoptosis (XIAP) and B-cell lymphoma-extra large (Bcl-x(L)) IRESes and inhibits IRES-dependent translation of both messages. Therefore degradation of this repressor upregulates XIAP and Bcl-x(L) IRES activity resulting in enhanced expression of both proteins (Liwak, Thakor et al. 2012).

Another signaling event has been proposed to upregulate IRES activity during the

G2/M phase of the cell cycle. Novel phosphorylation sites have been identified on mTOR complex 1 (mTORC1), the raptor protein. Cyclin-dependent kinase 1 (CDK1) and glycogen synthase kinase 3 (GSK3) pathways have been implicated in phosphorylation of these mTORC1 sites during G2/M specifically, resulting in altered mTORC1 activity

(Ramirez-Valle, Badura et al.2010). One example of this “altered activity” is enhancement of rapamycin resistance IRES-dependent translation during mitosis.

Enhanced protein expression of c-myc and ornithine decarboxylase (ODC) was dependent on phosphorylation of these novel mTORC1 sites in G2/M synchronized cells.

These proteins are synthesized from IRES containing messages (Stoneley, Paulin et al.

1998; Pyronnet, Pradayrol et al. 2000). Unfortunately, experiments to show increased expression of these specific proteins resulted from enhanced IRES activity of their messages were not performed. This group did demonstrated that upregulation of IRES activity of the EMCV IRES in G2/M synchronized cells was dependent on phosphorylation of these novel mTORC1 sites. However, claiming this signaling event leads to increased IRES activity of all cellular IRESes is premature. Testing IRES activity

of cellular IRESes (particularly those known to be upregulated during G2/M like ODC,

p58PITSLRE or p27KIP (Cornelis, Bruynooghe et al. 2000; Pyronnet, Pradayrol et al. 2000;

Miskimins, Wang et al. 2001)) is clearly needed.

IRESes and disease

Many diseases, such as AIDS, hepatitis C, and cancer (Zemel, Issachar et al.

2011; Reynolds, Kaminski et al. 1995; Attal, Theron et al. 1996), are caused by viruses that translate their messages in an IRES-dependent manner. Therefore studying IRES- dependent translation of viral messages could lead to novel drug development for fighting these diseases. Activity of cellular IRESes has also been implicated in contributing to disease, ranging from neurodegenerative disease such as Alzheimer’s (Beaudoin, Poirel et al. 2008; Veo and Krushel 2009) to varying types of cancers (Montanaro, Calienni et al. 2010; Petz, Them et al. 2012; Yoon, Peng et al. 2006; Braunstein, Karpisheva et al.

2007; Ishimaru, Ramalingam et al. 2009; Ruggero 2009). Although studying cellular

IRESes is particularly challenging due to a lack of common sequences or structure, understanding how these IRESes are regulated would be highly beneficial to our understanding of the etiology of these illnesses and to identifying novel targets to treat them.

IRES-mediated translation initiation has been link to cancer etiology (Montanaro,

Calienni et al. 2010; Petz, Them et al. 2012; Yoon, Peng et al. 2006; Braunstein,

Karpisheva et al. 2007; Ishimaru, Ramalingam et al. 2009; Ruggero 2009). A general mechanism regulating activity of all cellular IRESes has not been found but the regulation of certain cancer associated IRESes has been identified. There is evidence suggesting a switch from cap-dependent translation to cap-independent translation in

response to hypoxic conditions. Under these conditions IRES activity from Hif-1α,

VEGF 5’ leaders increased lead to enhanced expression of both proteins and tumor angiogenesis. This switch is due in part to increased 4E-BP1 and eIF4G expression

(Braunstein, Karpisheva et al. 2007). Genotoxic stress, by ethylmethane sulphonate or mitomycin C, can switch on the oncogenic c-MYC IRES. Activation of the p38 and

MAPK/ERK signaling pathways is required under these conditions for increased IRES activity and c-MYC expression (Subkhankulova, Mitchell et al. 2001). Another example of a switch from cap to IRES-dependent translation is shown to inhibit cancer development. During oncogene-induced senescence, a switch from cap to IRES- dependent translation occurs, upregulating IRES activity of the p53 5’ leader and p53 protein expression. This switch is dependent on expression of DCK1, the gene associated with X-linked dyskeratosis congenital that modifies ribosomal RNA by pseudouriylation

(Bellodi, Kopmar et al. 2010).

Additionally, IRES-mediated translation has been linked to the appearance of resistant cancer cells after the initial success of cytotoxic therapeutic treatment. IRES- dependent translation often escapes control mechanisms that are utilized by the rest of the cellular mRNAs. Therefore this mechanism has been implicated in allowing some cells to escape pro-apopotic signals during treatment (Holcik 2004). Indeed, an enhancement of

IRES activity is often seen in response to these therapies.

In this dissertation I will describe internal translation initiation of two eukaryotic mRNAs and how misregulation of this mechanism contributes to two otherwise unrelated conditions. The first part of the thesis illustrates the relationship between translational regulation of the FMR1 mRNA via an IRES and fragile X associated syndromes. The

second part of the thesis identifies internal translation initiation as is a major contributor

to over-expression of the oncoprotein Aurora A in immortalized cells. In an attempt to

identify novel targets for the development of anticancer drugs, I explore the regulation of

Aurora A IRES activity in cell lines.

Fragile X Syndrome

Fragile X Syndrome (FXS) is the most common form of inheritable mental

impairment, ranging from learning disabilities to mental retardation (Warren and Nelson

1994; Jin and Warren 2000). FXS was first described in 1943 by J. Purdon Martin and

Julia Bell whose family included eleven severely mentally impaired male members

(Glass 1991). However, it wasn’t until the first diagnostic test for FXS was developed in

the 1970s before research of the disorder truly commenced (Sutherland 1977). FXS

clinically presents with seizures (epilepsy), attention deficit and hyperactivity, anxiety

and unstable mood, and/or autistic-like behaviors. Patients may also exhibit mildly

abnormal facial features, such as a long face and large ears, as well as flat feet and

hyperextensible joints. Other physical effects include potential heart murmurs and

macroorchidism (Warren and Nelson 1994; Jin and Warren 2000). As its name implies,

FXS is associated with a “fragile” site at chromosome Xq27.3 caused by a large trinucleotide (CGG)n repeat expansion within the highly conserved fragile X mental retardation-1 (FMR1) gene (Kremer, Pritchard et al. 1991; Verkerk, Pieretti et al. 1991;

Yu, Pritchard et al. 1991). It is a maternally inherited, X-linked dominant trait thereby it affects males to a greater extent than females (Jin and Warren 2000).

Molecular mechanisms of FXS

FXS is one of approximately 20 trinucleotide repeats disorders identified in humans. Repeat expansions of these disorders can be found anywhere along the gene. For example the CAG repeats that define Huntington’s disease are located in the ORF of the

Huntingtin gene (HTT) (Albin and Tagle 1995). In mytonic dystrophy, the CTG repeats are located in the 3’UTR of the dystrophia myotonica protein kinase (DMPK) allele

(Salvatori, Fanin et al. 2005). The CGG repeat expansion found in FXS resides in the 5’

UTR of the FMR1 gene. Normally this allele contains approximately 5- 60 CGG repeats in humans (Table 1.2). There is a pre-mutation identified by the expansion of the CGG trinucleotide up to 230 repeats. During maternal transmission, this pre-mutation can undergo a DNA repair-dependent expansion into a full mutation of greater than 230 repeats (Reyniers, Vits et al. 1993). A person with the full mutation will present with

FXS characteristics. However, the expansion of the CGG repeats itself is not responsible for the FXS phenotype (Hinds, Ashley et al. 1993). The FMR1 gene is silenced due to the creation of a condensed and transcriptionally inactive chromatin structure formed from hypermethylation of the CpG island followed by histone deacetalyation (Oostra and

Chiurazzi 2001). Consequentially, expression of the FMR1 gene product, the fragile X mental retardation protein (FMRP) is inhibited resulting in misregulated expression of many genes.

Physiological functions of FMRP

FMRP is expressed in many different tissues but it is most abundant in the brain and testes (D'Hulst and Kooy 2009). The protein is comprised of two hnRNP K

Table 1.2 The physical and behavioral effects of the CGG trinucleotide repeat expansion of the FMR1 gene on the X chromosome # of CGG repeats Phenotype Normal Allele 5-60 Normal Pre-mutation Allele 60-230 Range from normal to mild forms of physical and/or behavioral FXS characteristics with greater effects correlating to increased expansion number. 50% of males will develop neurodegenerative disease in later life. Full mutation Allele ≥230 A spectrum of FXS characteristics including mental retardation, large body size, macroorchidism, long face, prominent chin, large ears, flat feet, hyperextensible joints, autistic like behaviors (poor eye contact and stereotypic movements), attention deficit hyperactivity disorder, speech and language problems, epilepsy and heart murmurs. Characteristics are more severe in full-methylated full mutation FXS versus partial-methylated full mutation mosaic FXS.

homology (KH) RNA- binding motifs, a nuclear localization signal (NLS), a nuclear

export signal (NES), and two coiled coils (CC) that are involved in protein-protein

interactions. In addition FMRP contains a second RNA-binding motif, an RGG box that binds G-quartet structures of mRNA (Siomi, Siomi et al. 1993).

FMRP is involved in various mechanisms that are important for proper brain development and function. This protein plays a crucial role in nucleocytoplasmic trafficking as well as localizing mRNA to the synapse (Antar, Dictenberg et al. 2005). A large number of FMRP neurospecific mRNA targets have been identified including the

FMR1 mRNA (Ashley, Wilkinson et al. 1993; Siomi, Siomi et al. 1993). FMRP directly binds a canonical FMRP-binding site found in the 3’UTR of the mRNA targets (Antar,

Afroz et al. 2004). This interaction not only localizes targets to the synapse but plays an important role in regulating synaptic protein synthesis (Figure 1.6). FMRP can also directly bind cytoplasmic FMR1 interacting protein 1(CYFIP1) which in turn binds the eukaryotic initiation factor 4E. Formation of the FMRP-CYFIP1 complex leads to downregulation of cap-dependent translation initiation of FMRP mRNA targets, (Napoli,

Mercaldo et al. 2008). In addition, the FMRP-CYFIP1 complex can protect dendritically localized mRNA from degradation (De Rubeis and Bagni 2010). In response to neuronal activity the complex can be disrupted allowing for local de novo translation of the mRNA target. This process is required for synaptic plasticity. Conversely, FMRP may assist the

RNA induced silencing complex (RISC) in identifying specific mRNA targets for microRNA (miRNA) and/or small interfering RNA (siRNA) gene regulation (Jin, Alisch et al. 2004). This hypothesis is based on the finding that FMRP interacts directly with both RISC and the 3’UTR of its mRNA targets, the most common location for a miRNA binding site in metazoans (Jin, Alisch et al. 2004; Qurashi, Chang et al. 2007). It is misregulation of these different post-transcriptional mechanisms due to the loss of FMRP expression that contribute to the dendritic development and neurotransmission issues seen fragile X patients (Muddashetty, Kelic et al. 2007) .

Figure 1.6: Fragile X mental retardation protein (FMRP) function in neurons FMRP (orange triangle) dimerizes in the cytoplasm and enters the nucleus by its nuclear localization signal. FMRP forms a messenger ribonucleoprotein (mRNP) complex, by interacting with specific RNA transcripts (blue squiggle) and proteins. The mRNP complex is transported out of the nucleus by the FMRP nuclear export signal. Once in the cytoplasm, the mRNP complex can interact with the RNA-induced silencing complex (purple star) and other proteins such as CYFIP1. Both mRNP complexes (with or without RISC) can be transported into dendrites before associating with ribosomes and can regulate protein synthesis (string of blue circles) in response to synaptic stimulation signals such as activation of the metabotropic glutamate receptor (red oval) by glutamate (red circles).

In neurons, FMRP is associated with polysomes at the base of dendritic spines in an RNA and microtubule dependent manner (D'Hulst and Kooy 2009). Dendritic spines usually receive excitatory input from the single synapse of an axon. A correlation between the induction of synaptic plasticity (the ability of the connection between two neurons to change in strength by either long term depression (LTD) or long term potentiation (LTP) in response to neuronal activity) and the number and/or shape of dendritic spines has been identified (Yuste and Bonhoeffer 2004). Indeed, the major morphological alteration in the brain seen in both FXS mouse models and postmortem in

FXS patients is the formation of immature dendritic spines (Hinds, Ashley et al. 1993;

Van Dam, D'Hooge et al. 2000). This feature indicates a defect in the dendritic pruning during development.

There are potentially 12 isoforms of FMRP, containing different functional domains, generated by alternative processing of the 3’terminal of the single FMR1 gene

(Siomi, Siomi et al. 1993). The occurrence and function of the individual isoforms are not known, but all splice variants are associated with the polysome suggesting each transcript is actively translated (Tamanini, Meijer et al. 1996; Willemsen, Bontekoe et al. 1996).

Studying the functions of these isoforms could prove beneficial in our understanding of the pathogenesis of this syndrome. Additionally, better therapeutic approaches may be discovered to improve the lives of FXS patients.

The mGluR theory and the GABAAR theory

The FMR1 knockout (KO) mouse model exhibits learning deficits, altered sensorimotor integration and mildly enhanced locomotor activity like FXS patients (Van

Dam, D'Hooge et al. 2000). An increase in metabotrope glutamate receptor (mGluR)-

dependent LTD in the hippocampus of these mice has been indicated by electrophysiological testing. These finding are significant since LTD and LTP are

involved in learning and memory. The cognitive deficits seen in FXS can be related to

these abnormal observations. Activation of postsynaptic group 1 (GP1) mGluRs

(mGluR1 and mGluR5) requires rapid translation of pre-existing dendritically localized

mRNAs such as the FMR1 mRNA (Weiler, Irwin et al. 1997). mGluR activation leads to

the synthesis of proteins that stabilize LTD, including FMRP (Huber, Kayser et al. 2000).

It has been postulated that newly synthesized FMRP inhibits synthesis of its target

mRNA, including the FMR1 mRNA, that stops LTD (Figure 1.7) (D'Hulst and Kooy

2009). This theory suggests enhanced mGluR-dependent LTD and/or mGluR function are

responsible for many features of the FXS phenotype. Indeed, crossing FMR1 KO mice

with mice containing a mutant murine functional homologue of the human gene encoding

mGluR5 (GRMS) resulted in a 50% reduction of mGluR5 activity and rescues many of

the FXS abnormalities (Dolen, Osterweil et al. 2007).

Improvements with behavior and memory issues in FMR1 KO mouse, fly, and

zebrafish models by mGluR5 antagonists 2-methyl-6-(phenylethynel)-pyridine (MPEP)

and fenobam have been demonstrated (McBride, Choi et al. 2005; Yan, Rammal et al.

2005; Tucker, Richards et al. 2006). Fenobam is an orphaned drug that was used to treat

anxiety in humans (Pecknold, McClure et al. 1982). Clinical trials with fenobam in FXS

patients reported some improvement in the patient’s mood warranting further

investigation (Berry-Kravis, Hessl et al. 2009). To date, only one mGLuR antagonist,

AFQ056, has shown statistically significant improvements of behavioural symptoms in

adults with the full-methylated full mutation. No improvements were detected in the less

Figure 1.7: The Excitatory/Inhibitory (E/I) imbalance of FXS The integration of excitatory and inhibitory input at the level of the individual neuron is essential to the information processing that mediates brain function. Excitatory synapses (regulated by glutamate signaling) form at the dendritic spines while inhibitory synapses (regulated by GABA signaling) reside along the dendritic shaft (Gatto and Broadie 2010). FMRP appears to be a key component in maintaining a proper balance of E/I signaling required for healthy neuronal development. Dendritically localized protein synthesis required for mGlu-dependent LTD is enhanced in response to excitatory signaling resulting in increased expression of both FMRP mRNA targets and FMRP itself. FMRP downregulates dendritic protein synthesis thereby stopping LTD. Loss of FMRP expression in FXS results in the formation of an abnormally large number of dendritic spines indicating elevated excitatory synaptogenesis (Yuste and Bonhoeffer 2004). In addition, loss of FMRP expression results in decreased inhibitory signaling (Chang, Bray et al. 2008; D'Hulst, Heulens et al. 2009). In response to these findings two therapeutic approaches have been developed: The mGluR theory suggests treating FXS patients with mGluR antagonist to restore the E/I balance while the GABAA R theory attacks the problem from the other direction suggesting patients be treated with drugs that elevate inhibitory signaling.

impaired mosaic-FXS patients (Levenga, Hayashi et al. 2011). These patients have the

full mutation only it is partially-methylated. They do express some level of the FMR1 mRNA and FMRP so perhaps mGluR signaling is not elevated enough to induce a noticeable affect with this drug.

Dysfunction of the gamma-Amino Butyric acid (GABA)ergic system has been

suggested to contribute to the FXS phenotype (Figure 1.7). GABA is an amino acid

derived from glutamate. GABA and glutamate have opposing functions in the central

nervous system as inhibitory and excitatory neurotransmitters, respectively (Petroff

2002). Low GABA activity has already been linked to several behavioural conditions

found in FXS patients including anxiety, hyperactivity, epilepsy, autism spectrum

disorder, and insomnia (D'Hulst and Kooy 2007). A dysfunctional GABAergic system

has been shown to affect learning and memory as well (D'Hulst and Kooy 2009).

Numerous studies have demonstrated the presence of FMRP in glutamatergic

(excitatory) neurons (Huber, Gallagher et al. 2002; Antar, Afroz et al. 2004; Tervonen,

Louhivuori et al. 2009). FMRP has also been found in nonneuronal cell types such as

glial fibrillary acidic protein (GFAP)+ or NG2+ glia (Pacey and Doering 2007). In

contrast, very little attention has been focused on the study of FMRP expression within

GABAergic cells.

The first experimental proof for targeting the GABAergic pathway involved a

study with FMR1- / - flies. These flies die during development when fed a diet containing

high levels of glutamate (Chang, Bray et al. 2008). A library screen of 2000 chemicals

was performed to identify molecules that could rescue lethality. Three of the nine

molecules that did rescue lethality are part of the GABAergic pathway (Chang, Bray et al. 2008).

Although only one example of pharmacological rescue exists, clinical studies for treating FXS patients with GABAergic agonists are underway. The pharmalogical effects of some GABAA receptor agonists, most commonly the benzodiazepines (BZD) are

already known. Diazepam, a BZD agonist, is a proven anxiolytic drug but it also causes

many side effects (D'Hulst and Kooy 2009). Therefore, partial GABAA receptor agonists

are being considered for clinical trials (Atack 2003).The neuroactive steroid ganaxolone, an allosteric modulator of the GABAA receptor, has been shown to safely treat catamenial epilepsy in phase II trials and has also successfully treated seizures in FMR1 KO mice

(Reddy 2004). As a result trials with ganaxolone for seizure prone FXS patients are being

developed (Cornish, Turk et al. 2008).

The pre-mutation allele

Due to the lack of obvious FXS characteristics in the mothers of FXS patients, it

was assumed carriers were unaffected by the 60-230 CGG repeat pre-mutation. Some

mild cognitive and psychiatric disabilities, for example anxiety and depression, were

detected in these mothers. However, physicians initially attributed these conditions to the

stress of raising a child with special needs (Loesch, Hay et al. 1994; Sobesky, Taylor et

al. 1996). In the early 2000s, doctors recognized that some of the female carriers had

aging fathers who presented with a unique set of symptoms including progressive

intention tremor, gait ataxia, parkinsonism and autonomic dysfunction (Hagerman,

Leehey et al. 2001). Soon the association between carrying the pre-mutation allele and

these symptoms became clear and this novel neurodegenerative condition was named

fragile-X-associated tremor/ataxia syndrome (FXTAS) (Berry-Kravis, Lewin et al. 2003;

Jacquemont, Hagerman et al. 2003; Leehey, Munhoz et al. 2003). A closer look at the

carrier mothers revealed a correlation between the number of repeats in the pre-mutation

allele and the presence of subtle physical features of FXS (prominent ears and flexible

finger joints) and other conditions such as pre-mature ovarian failure (Table 1.2)

(Sherman 2000; Sullivan, Marcus et al. 2005; Bodega, Bione et al. 2006). It was

determined that presence of emotional problems in these mothers also correlated with the

number of CGG repeats (Figure 1.8) (Johnston, Eliez et al. 2001).

Molecular mechanisms of the pre-mutation allele

The mechanisms that contribute to the FMR1 pre-mutation allele phenotype are still unclear. Although an association exists in both male and female carriers between the presence of physical and cognitive phenotypes and the level of FMRP expression

(Tassone, Hagerman et al. 2000; Kenneson, Zhang et al. 2001), female carriers rarely go on to develop FXTAS (Berry-Kravis, Lewin et al. 2003; Jacquemont, Hagerman et al.

2004). Additionally, children with FXS do not develop this neurodegenerative disorder as they age.

Interestingly, transcript levels correlate inversely with protein levels in the pre-

mutation range of 60-230 repeats. FMR1 mRNA levels increase as the number of repeats

increases but protein levels drop off (Figure 1.8) (Tassone, Hagerman et al. 2000;

Kenneson, Zhang et al. 2001). This phenomenon suggests the presence of a feedback

loop between transcription and translation of the FMR1 gene. It also begs the question: is

aberrant expression of FMRP and/or FMRI transcripts containing a high number of CGG

repeats contributing to the variations in pre-mutation phenotypes? There is evidence

Figure 1.8: The relation between CGG repeats in the pre-mutation range and possible effects for the pre-mutation carrier As the number of CGGs increase in the pre-mutation range of 60-230 repeats, there is an increase in the number of FMR1 transcripts and total number of transcribed CGG repeats. However, the level of FMRP decreases. Carriers of the allele at the higher end of this range have a greater chance of possessing FXS-like phenotypes and males, almost exclusively, are at a higher risk for developing FXTAS. Why transcription is enhanced at the higher end of the pre-mutation range but translation is inhibited is unclear. In addition, the cause(s) of the FXS-like phenotypes and FXTAS is unknown.

suggesting increased expression of the FMR1 transcript can lead to cellular atrophy.

However, cell loss is not due to the number of mRNA molecules themselves but rather

the total number of transcribed CGG repeats (Jin, Zarnescu et al. 2003). Observing eye

development in flies in the presence of GFP-encoding transcripts with varying numbers

of CGG repeats in the 5’UTR showed a smaller number of mRNA transcripts with high

CGG repeats were more damaging than a higher number of mRNA molecules with no

repeats. In fact, high transcript numbers without CGG repeats did not affect eye

development at all. Also, comparing high to low transcript expression with

transcriptscontaining the same number of CGG repeats showed the higher expression levels were more damaging. These results suggest that increased expression of the CGG repeats in the absence of an increased number FMR1 transcripts or aberrant expression of

FMRP can contribute to neurodegeneration and may be the primary contributor to the development of FXTAS.

How increased numbers of CGG repeats in the 5’UTR of the FMR1 mRNA results in cell death is not understood. The inverse correlation between pre-mutation mRNA levels and protein levels suggests a decrease of translation initiation of the mRNA. Another possibility is the CGG repeats may sequester RNA-binding proteins and indirectly affect regulation of other RNAs. Indeed, the expansion of the CUG trinucleotide repeat in the 3’UTR of the myotonic dystrophy protein kinase (DMPK) mRNA does just that. The nuclear-located mutant DMPK transcripts attract RNA- binding proteins that results in defective mis-splicing of several cellular transcripts

(Mastroyiannopoulos, Shammas et al. 2010). Either way, the expansion of this repeat is detrimental to humans as demonstrated by both FXTAS and fragile X syndrome.

Questions

Why have these CGG repeats been evolutionarily conserved? The fact that they are evolutionarily conserved in mammals suggests the repeats have some function aside from inhibiting transcription and translation of the FMR1 gene (Eichler, Kunst et al.

1995). The location of the repeats in the 5’UTR of the FMR1 mRNA suggests these repeats may be a transcription factor binding site. There is a positive correlation between increased transcript levels and CGG repeats in the pre-mutation range. Are the repeats acting as a transcription enhancer element? Perhaps they affect RNA stability. mRNA transport is another possible function of the CGG repeats in the 5’UTR.

The inverse correlation between mRNA and protein levels in FXTAS patients suggests these repeats have a regulatory role in translation initiation. It has also been suggested that the FMR1 5’ leader can be translated by both a cap-dependent and IRES- dependent mechanisms (Chiang, Carpenter et al. 2001). In this study my goal was to validate the presence of an IRES in the 5’ leader of the FMR1 transcript, to identify regions in the FMR1 5’ leader critical for IRES activity, and to determine if FMR1 IRES activity is affected by cellular processes in which FMRP participates. I also wanted to determine if the CGG repeats play a role in regulating internal initiation of the FMR1 transcript.

Defining Cancer: A History of Theories from Ancient to Modern Times

Cancer greatly predates the existence of human beings on earth. The oldest depictions of this disease are evident in the fossilized bone tumors of prehistoric animals.

Indeed, humans have been fighting cancer throughout recorded history. The first historical account of a human cancer was cited around 3000 BC. The author of the Edwin

Smith Papyrus described a dire condition of a protruding mass of the breast with no known treatment (Breasted 1930). The second renowned documentation of human cancer was written in the Ebers Papayrus over a thousand years later. It contained the first known depiction of soft tissue tumors and fatty tumors along with possible references to skin, uterine, stomach and rectum cancer (Ebbell 1937). However, it was circa 375 BC in ancient Greece, during a period known for the blending of science and art, before the first theory attempting to describe cancer and its treatment was brought to the forefront of medicine by Hippocrates and his followers (Hajdu 2011; Morrison 2010; Papac 2001).

The Humoral Theory

Hippocrates, known as the “Father of Medicine” was the first to dispute that superstition caused cancer, suggesting it was the result of an imbalance of bodily secretions. Humorism, thought to have originated in ancient Egypt, is a theory which recognizes the presence of four humors or fluids in the human body that are responsible for the overall health and temperament of an individual (Sertima 1992). The four humors of humoral medicine are black bile (Gk. melan chole), yellow bile (Gk. chole), phlegm

(Gk. phlegma), and blood (Gk. haima). When all four humors are balanced a person is mentally and physically healthy (Yapijakis 2009). However, an imbalance of the humors results in physical and psychological disease and disabilities. For example, accumulation of thick black bile was considered the cause of incurable ulcerative cancer and thin yellow bile was responsible for curable nonulcerative cancer (Hajdu 2011; Morrison

2010; Raven 1990).

It was also during this period when Hippocrates termed the first words to define different cancers. Carcinos, the Greek word for crab, was used to describe ulcerated

45 malignant tumors (he thought tumor growths resembled crab movements), carcinoma represented malignant tumors, and scirrhus meant a hard tumor with uncertain malignant probability (Hajdu 2011). Three hundred and fifty years later, Aulus Celsus of Rome (25

BC – 50 AD) declared Latin the official language of medicine thereby changing the

Greek word carcinos to the Latin word cancer. Author of De Medicina (thought to be the only surviving section of a much larger encyclopedia), Celsus is credited for the first observation of metastasis when he recognized breast cancers would often reoccur in the axillary region and could spread to other distant organs (Hajdu 2004).

The recognition of humoral medicine by a famous Greek surgeon working in

Rome named Claudius Galen (130-200 AD) was blamed for hundreds of years of misdirected progress toward understanding cancer development. Even though a surgeon to the gladiators, Galen refused to utilize surgical intervention to treat cancer in most cases, insisting the best remedy was the removal of black bile by means of purging medicines (Major 1954). This form of medical intervention was unchallenged for over

1300 years. It was not considered threatening by the religions of the time. Also, the study of the human body by such means as autopsies or treatment by surgery was highly taboo and therefore forbidden – unless of course you were an injured gladiator. It wasn’t until the beginning of the 15th century, during the Renaissance period, that scientists began to have a better understand of the workings of the body by applying the scientific method to study disease.

The foundation for scientific oncology: a pathological approach

Although the ideology of humorism remained largely accepted, studies relating disease to human pathology resulted in the rejection of humoral theory by numerous

physicians throughout the centuries. Lanfranc of Milan (1252-1315) and Henri de

Mondeville (1260-1320) are recognized for their individual contributions towards

understanding the different types of tumors as well as their rejection of Galen’s humoral

theory. Lanfranc, the founder of French surgery, was the first to determine how to

differentiate between benign and malignant breast tumors. Mondeville was the first to

publicly reject humoral medicine. Also, he concluded that scirrhus and carcinoma was

actually the same thing (Hajdu 2011). These early rejections of humoral ideology, in

conjunction with the first public autopsies of two human bodies in Italy in 1315 and the

invention of movable-type printing signaled the end of the Dark Ages and the beginning

of the Renaissance era of medicine (Hajdu 2011).

Celsus’ De Medicina was used to create the original printed medical book in

1478, quickly followed by several other ancient medical writings. De Abditis, published

in 1507, contained the first printed case report of a cancer, along with other cases, by the

Italian physician Antonio Benivieni. Benivieni had a relative whom he unsuccessfully

treated for ‘vomiting and wasting’. Autopsy revealed the patient suffered from what is

now called a gastric carcinoma with pyloric obstruction (Benivieni 1507).

It was Giovanni Morgagni of Padua (1682-1771) who over two hundred years

later thought to performed autopsies with the intention of locating pathological causes

directly relating to a patient’s disease. This idea is considered the foundation for scientific

oncology (Morrison 2010). Advancements in technology, most notably the invention of

the compound microscope, resulted in large steps forward in the quest to comprehend

cancer. Rudoph Virchow (1821-1902), a German physician, founded the field of microscopic pathology and was known to incessantly encourage his medical students to

“think microscopically.” He also introduced cell theory which states that cells are the

basic units of structure for all living things and that each cell comes from a pre-existing cell exactly like it (although Virchow essentially stole the idea of cell division from his former colleague Robert Remak) (Magner 1994). These new theories of cellular pathology are credited for pushing research toward the modern age. Even so, humoral medicine did not completely disappear. It is still practiced today as a popular alternative to modern medicine.

Theories from the 18th and 19th centuries

Humoral theory was just one of many theories throughout history that attempted to define cancer and its causes. Zacutus Lusitani and Nicholas Tulp, two 15th century

Holland doctors, suggested infection caused cancer. Infectious disease theory implied that

cancer was contagious and resulted in the isolation of patients from populated areas. In

1779, the first ever hospital dedicated exclusively for cancer patients (established in 1774

Rheim, France) was forced to move their patients to a different hospital outside of the

city due to the residents’ fear of infection (Morrison 2010). Today it is accepted that

cancer itself is not contagious. Still, these doctors weren’t completely off track as some

viruses and bacteria have been shown to increase a person’s risk of developing cancer

such as human papillomavirus (HPV), the gastric bacterium Helicobacter pylori and the

hepatitis B and C viruses (Klingelhutz and Roman 2012; Zabaleta 2012; Zemel, Issachar

et al. 2011).

Another popular idea was purposed by two medical authors in 18th century

Germany, Georg Ernst Stahl and Freidrich Hoffman. Their lymph theory suggested

cancer was made up of “fermenting and disintegrating” lymph varying in density, acidity,

and alkalinity. It was further supported by John Hunter (1728-1793), a renowned Scottish

surgeon who established that tumors grow from lymph discarded by the blood (Peyrilhe

1776). Next was the blastema theory which was defined by 19th century German

pathologist Johannes Muller. He proposed that cancer was made up of cells instead of

lymph. However, he did not believe that cancer cells came from normal cells but instead

arose from budding elements or blastema between healthy tissues (Gallucci 1985;

Diamandopoulos 1996). It was Muller’s student, Virchow, who determined that all cells,

even cancerous ones, are derived by other cells. Even though many of Virchow’s ideas

were great contributions to modern research some of them missed the mark. He

formulated the chronic irritation theory which simply stated cancer was cause by chronic

irritation. He mistakenly believed that cancer spread through the body like a liquid

instead of the spread of malignant cells as first shown by German surgeon Karl Thiersch

in the 1860s (Gallucci 1985; Diamandopoulos 1996). From the late 1800s through the

1920s the trauma theory, which suggested injury to be the cause of cancer, was very

popular. This theory was strongly supported even though injury was never shown to

cause cancer in lab animals (Gallucci 1985; Diamandopoulos 1996). Each of these

theories was eventually discredited by the scientific method. Still, contributions from the

scientists who proposed them have guided us to an ever closer understanding of this

dreadful disease.

The modern definition of cancer

Historically speaking, the accumulation of knowledge from the past century regarding the causes of cancer and how to treat it has been impressive. Innovative advancements such as the utilization of cancer causing agents (carcinogens) to induce

49 disease in lab animals as first demonstrated by Japanese scientists Katsusaburo

Yamagiwa and Koichi Ichikawa in 1915 (Rodricks 1994), the discovery of the chemical structure of DNA by James Watson and Francis Crick in 1953 (Watson and Crick 1953), and the identification of the first oncogenes and tumor suppressor genes by numerous scientists in the 1970s have contributed to the modern definition of cancer and its causes.

Cancer is currently defined as a heterogeneous disease that results from genetic damage by carcinogens or inherited genetic variations leading to an abnormal group of cells that can survive an increasing number of genetic mutations. A single tumor can be comprised of cells at different stages of cellular transformation that may have derived from separate origins. These cells adapt in response to the extracellular matrix consisting of a variety of cell types including stromal cells (fibroblasts and epithelial cells), endothelial cells and smooth muscle cells (making up the vasculature component), and immune cells such as dendritic cells and lymphocytes. Each of these cell types contribute to solid tumor growth, invasiveness, malignancy and metastatic growth (Radisky, Hagios et al. 2001; Bissell and Labarge 2005).

Cancers are categorized into four groups according to the origin of the transformed cells. Sarcomas are relatively rare cancers of mesenchymal origin including bone, fat, muscle, cartilage, vascular, and hematopoietic tissues. Carcinomas, the most common type of cancer, arise from epithelial cells to form breast, lung and colon malignancies. Lymphomas describe cancer originating from lymphocytes. And finally, leukemias are cancers derived from blood cells and do not form solid tumors.

Much has been learned about cancer and its development throughout history but treating it continues to be extremely difficult. It is clear there is still much more to learn

50 concerning the complexity of cancer. However, continuing advancements in scientific research are leading to new ideas regarding not only treatment and cure but also prevention of the numerous variations of this illness which has plagued human beings from the beginning.

Molecular Mechanisms of Cancer Development

Discovering successful treatments to cure human malignancies has been an immense challenge for physicians and scientists for thousands of years. The slow progress has contributed to the fear and frustration of many people around the world.

Even today patients often wait too long for optimal intervention due to the long held belief that cancer is incurable and treatment is worse than the condition itself. The main goal of current cancer research is to discover new ways to improve existing therapies and to identify new targets with which to develop new anti-cancer treatments. My research focuses on identifying and studying molecular mechanisms that contribute to cancer development and progression.

The Central Dogma and cancer research: a small overview

Studying the history of cancer research reveals a huge jump forward in our understanding of the disease since Francis Crick first defined the relationship between the informational macromolecules: DNA, RNA and protein. He formulated his “Central

Dogma” in 1958 based on the following observations. First in 1944, DNA was declared a major component of genetic material (Crick 1958) After solving the structure of DNA in

1953, Crick and James Watson demonstrated that DNA had the ability to replicate. They determined the two strands of DNA when separated could generate complementary copies of themselves due to adenine pairing only with thymine and guanine only with

51 cytosine. In 1954 George Gamow proposed that the sequence of proteins was directly determined by DNA (Judson 1996). However, it was known that chromosomes were located in the nucleus and proteins were made in the cell body. Also a correlation between the abundance of RNA in the cytoplasm and the rate of protein synthesis had been established. But the instability of RNA suggested this molecule would not tolerate the rapid changes of protein synthesis that was observed in the cell. Although microsomes (now called ribosomes) consisting of RNA and protein often formed at the same place where protein synthesis occurred. In addition, there wasn’t a mechanism connecting DNA to RNA. These puzzling observations lead to complex models that attempted to piece them all together (Thieffry and Burian 1996). In contrast Crick proposed a relatively straightforward idea (Crick 1958):

This states that once ‘information’ has passed into protein it cannot get out again. In other words, the transfer of information from nucleic acid to nucleic acid or from nucleic acid to protein may be possible, but transfer from protein to protein or from protein to nucleic acid is impossible. Information here means the precise determination of sequence, either of bases in the nucleic acid or of amino acids in the protein.

This idea was termed the Central Dogma of Molecular Biology, or simply “DNA makes RNA makes Protein.” Gene expression was defined as a process of transferring information encoded in genes in the DNA of every cell. This process utilizes proteins acting as "molecular machines" to copy (transcribe) genes into RNA messages. The messages are modified and exported from the cell nucleus into the cytosol where they are decoded (translated) to build specific proteins. This hypothesis has been challenged and modified over the years. Information from RNA to DNA is possible as demonstrated by reverse transcriptase. Prions replicate by a protein-only mechanism (Prusiner 1982).

Regardless, this one hypothesis led to the discovery of many mechanisms utilized during the cellular process of transferring information.

Unfortunately, misregulation of any mechanism involved in the process of transferring genetic information can contribute to tumorigenesis. Duplication mutations and gene translocation during DNA replication can create proteins with novel function or whose function can no longer be regulated. Cancer can also result from aberrant expression of a functionally normal protein as a result of differential rates of transcription and/or translation. For example, the loss or reduced expression of breast cancer

(BRCA)1, BRCA2, or p53 protein dramatically increases susceptibility to tumorigenesis

(Moynahan 2002). Additionally, over-expression of transcription factors (Myc), kinases

(Polo-like kinase 1) and anti-apoptotic factors (Bcl2) can also lead to tumorigenesis

(Stoneley and Willis 2004; Ishimaru, Ramalingam et al. 2009; Studach, Rakotomalala et al. 2009). In this section, molecular mechanisms that transfer genetic information from

DNA to RNA to Protein and their contribution to cancer development will be reviewed.

DNA processes: genetic mutations

In 1914 Theodor Boveri determined that cancer can be triggered by chromosomal mutation (Morgan, Dudley et al. 2006). Every time a cell divides it has to copy and transmit the exact same sequence of 3 billion nucleotides to its daughter cells. DNA replicates with fairly high fidelity, but mistakes happen. Fortunately, cells utilize numerous mechanisms to recognize and repair virtually any alteration that may occur in the DNA sequence. If these changes are not corrected the cell will most often die.

However if the cell divides and enough mutations are acquired a cancer could form.

In eukaryotic cells, DNA replication initiates after mitosis with the recognition of

a distinct DNA sequence, an AT-rich origin, by the origin recognition complex (ORC).

Licensing or the loading of the DNA helicase, the maintenance of mini-chromosome

(MCM), and other proteins to form the pre-replication complex follows. Upon activation of Cdc7/Dbf4 kinases in late G1 phase, the helicase is activated and the replisome, containing the DNA polymerase, is loaded onto the DNA strand. As activation of replication occurs, any further licensing is inhibited, assuring only one round of replication, and the cells enter S phase (reviewed in (Bell and Dutta 2002).

During S phase DNA is replicated in a semiconservative manner, meaning each of the two strands of DNA serve as a template for the formation of a complementary strand.

After the creation of a primer, a short segment of RNA that is complementary to the template strand, DNA polymerase α extends the 3’ end of the new strand for the first 20

bases at which time Pol ε (leading strand) or Pol δ (lagging strand) take over. Extension

of the newly synthesized strand continues until an incorrect nucleotide is inserted. The

extending polymerase also has 3’-5’ exonuclease activity that can detect the mistake, remove the incorrect base, and replace it with the correct one (Bell and Dutta 2002). This process is called proofreading.

When an incorrect nucleotide is added to the growing strand, replication is stalled by the fact that the nucleotide's exposed 3′-OH group is in the "wrong" position.

Proofreading can repair up to 99% of these errors but the cell can use a second

mechanism to look for mismatched nucleotides as well as strand-slippages (the insertion

of too many or too few nucleotides) after replication. Mismatch repair (nucleotide

excision repair) reduces the final error rate even further. Incorrectly paired nucleotides

cause irregularities in the secondary structure of the final DNA molecule. During

mismatch repair, enzymes recognize and fix these deformities. However, if mistakes

remain, they will become permanent mutations because after the next cell division they are no longer recognized as errors (reviewed in (Friedberg 2006; Lief 2012).

A mutation known as a base-pair substitution forms when a single mismatch is overlooked. Base substitutions involving replacement of one purine for another or one pyrimidine for another (e.g., a mismatched A-A pair, instead of A-T) are known as transitions; the replacement of a purine by a pyrimidine, or vice versa, is called a transversion. Likewise, when strand-slippage replication errors are not corrected, they become insertion and deletion mutations (Friedberg 2006; Lief 2012).

Other DNA processes can result in genetic mutations. Exposure to ionizing radiation, free radicals, certain chemicals and stalled replication forks during DNA replication can cause DNA double-stranded breaks (DSBs). Genetic instability can occur if the cell is unable to respond properly to DNA DSBs. Eukaryotic cells use two separate mechanisms for DNA DBS repair–homologous recombination (HR) and non- homologous end-joining (NHEJ) (Figure 1.9).These pathways are conserved between yeast and vertebrates but their relative contribution to DSB repair varies greatly. HR plays a dominant role in DSB repair in yeast. In vertebrates, NHEJ make a larger contribution to repairing radiation-induced DSB (Sonoda, Hochegger et al. 2006).

In order to repair DSBs via HR an undamaged template molecule containing a homologous DNA sequence is needed. This template may be a sister chromatid (the homologous chromosome) or an adjacent repetitive sequence on the same chromosome.

A B

Figure 1.9 Repair pathways of DNA double-stranded breaks (A) NHEJ rejoins the two broken ends directly and generally leads to small DNA sequence deletions. It requires the DNA-end-binding protein Ku, which binds free DNA ends and recruits DNA-dependent protein kinase, catalytic subunits (DNA-PKcs). Xrcc4 and DNA ligase IV are recruited next. The Rad-50-Mre11-Nbs1 complex, which contains helicase and exonuclease activities, may also function in NHEJ, particularly if the DNA ends require processing before ligation. (B) HR requires Rad52, a DNA-ending-binding protein, and Rad51, which forms filaments along unwound DNA strand to facilitate strand invasion. The resected 3’ end invades a homologous DNA duplex and is extended by DNA polymerase. In meiotic cells, the ends are ligated by DNA ligase 1 and the interwound DNA strands (Holliday junctions) are resolved resulting in either crossover or non- crossover gene conversion products. Only one of the many recombinations is shown here. Recent data indicates that mitotic recombination is usually not associated with crossing over suggesting it may be coupled intimately with replication.

HR-dependent DSB repair involves strand resection of the break to form 3’ single-strand

(ss) overhangs. These overhangs interact with the recombination protein Rad52 and subsequently with polymerized Rad51 (Shinohara, Ogawa et al. 1993). The complex of

Rad51and ssDNA form heteroduplexes with intact homologous sequences with the help of Rad54 using either the DSBR pathway (sometimes called the double Holliday junction model) and the synthesis-dependent strand annealing (SDSA) pathway (reviewed in

(Symington 2002)). Homologous recombination is often called the error-free DSB repair mechanism since the result of HR should not alter the DNA sequence. However, the

DSBR pathway most often results in chromosomal crossover while SDSA always ends with non-crossover products (Symington 2002).

NHEJ of two double-stranded (ds) DNA ends does not require an undamaged partner or rely on homologies between the recombining ends. However, NHEJ can use small flanking homologies of 2-6 nt (Sonoda, Hochegger et al. 2006). NHEJ is initiated by DNA end-binding proteins Ku70 and Ku80, which rapidly associate with exposed

DNA breaks. Recruitment of the catalytic subunit of the DNA-dependent protein kinase

(DNA-PKcs) follows (O'Driscoll and Jeggo 2006). The Ku/DNA-PKcs complex ultimately recruits ligase IV, which completes the repair of the break (Grawunder, Wilm et al. 1997). NHEJ often results in sequence alterations by small deletions, insertions, or inversions. Thus the repair process itself is error-prone. DSBs in response to ionizing radiation have an increased chance to result in a genetic mutation since the use of NHEJ is greater compared to breaks caused stalled replication forks which is almost exclusively repair by the error-free HR pathways (Sonoda, Hochegger et al. 2006). Understanding

how the cell chooses between these mechanisms is a current area of study that may

provide insight into preventing the development of secondary cancers resulting from

current ionizing radiation therapies.

DNA processes: epigenetics

A new focus in cancer research regarding DNA processing is the field of

epigenetics. Epigenetics defines heritable changes in gene expression that occur in the

absence of genetic mutations. DNA methylation and histone covalent modification are

the two major mechanisms of epigenetics. These processes are interconnected since both

are involved in chromatin organization and regulate the accessibility of genes to the

transcriptional machinery. Additionally it has been suggested that these mechanisms are

dependent on each other (Egger, Liang et al. 2004). Therefore any alteration of one

mechanism could greatly affect the other. The resulting disruption of chromatin structure

could lead to misregulated expression of genes involved in carcinogenesis.

DNA methylation is catalyzed by a family of DNA methyltransferase enzymes

(DNMT’s). Cytosine followed by guanosine (a CpG dinucleotide) is the most common

target of DNA methylation. Almost all CpGs in the genome are methylated. However,

there are CpG “islands” associated with promoters that escape methylation (Egger, Liang

et al. 2004). The modification mainly represses transcription and contributes to genome

stability by maintaining silencing of transposable elements.

Acetylation, methylation, and phosphorylation are covalent post-translational

modification of histones (Santos-Rosa and Caldas 2005; Zhang and Dent 2005). Each

process utilizes specific enzymes to either add or remove a modification at an appropriate

location. Modifications usually associated with active genes are H3K4me3 and H3K9ac.

Enrichment of H3K9me2, H3K9me3, H3K27me2, and H3K27me3 modifications are

58 indicators of possible inactive genes. However, identification of these modifications alone can be misleading since active and inactive genes can have overlapping patterns

(Santos-Rosa and Caldas 2005; Zhang and Dent 2005).

Changes in DNA methylation and histone covalent modification can contribute to cancer in various ways. Hypermethylation of CpG islands at tumor suppressor genes switches off their expression. On the other hand, hypomethylation switches on expression of oncogenes. Global hypomethylation can result in genomic instability as well as inappropriate activation of transposable elements (Egger, Liang et al. 2004).

Increased or decreased acetylation and methylation can result in aberrant expression of tumor suppressor and oncogenes as well. Histone phosphorylation, particularly H3S10 and H3S28, are crucial regulators of the cell cycle and misregulation of these modifications by the Aurora kinases are often associated in cancers (Santos-Rosa and Caldas 2005; Zhang and Dent 2005). In addition, a number of factors including aging, diet, and environment have been suggested to influence these mechanisms (Feser and Tyler 2011; Okoji, Yu et al. 2002; Richardson 2003; Takiguchi, Achanzar et al.

2003; Rodenhiser and Mann 2006). The resulting changes can lead to tumorigenesis in the absence of genetic mutations.

Aberrant transcription

A major mechanism influenced by either genetic mutations or epigenomic changes is transcription - the transferring of genetic information from DNA to RNA.

Eukaryotic cells utilize three RNA polymerases to transcribe ribosomal RNA, non-coding

RNAs, and messenger RNA (mRNA). There are numerous events, some unique and

some overlapping, that regulate turnover of the different types of RNA. In this section I

am going to discuss regulatory mechanisms that control steady-state levels of mRNA.

Like translation, transcription is comprised of three steps: initiation, elongation,

and termination. The major regulatory step of transcription is initiation albeit elongation

and termination can also be regulated. Transcription initiation of mRNA requires the general machinery (RNA polymerase II (pol II) and the general transcription factors

(GFT)), DNA-binding proteins (trans-acting factors), and cis-acting elements (Dynan and

Tjian 1985; Ptashne 1986). Initiation begins with recognition of the pol II promoter by the GTF TFIID complex. The core promoter consists of two segments: the TATA box

(consensus 5′-TATAWAW-3′) located around -25 nucleotides and the initiator (Inr) sequence (consensus 5′-YYCARR-3′) located around nucleotide +1 (Novina and Roy

1996; Marr and Roberts 1997). TFIID is a complex made up of the TATA-binding protein (TBP) and at least 12 TBP-associated factors (TAFs) (Burley and Roeder 1996;

Green 2000). During transcription, TAFs assist in attachment of TFIID to the TATA box.

In conjunction with other proteins called TAF- and initiator-dependent cofactors (TICs),

TAFs also participate in recognition of the Inr sequence (Lee and Young 2000). After

TFIID has attached to the core promoter, the pre-initiation complex (PIC) is formed by attachment of the remaining GTFs (TFIIA, TFIIB, TFIIF/RNA pol II, TFIIE and TFIIH)

(Lee and Young 2000). The final step in assembly of the initiation complex is the addition of phosphate groups to the C-terminal domain (CTD) of the largest subunit of pol II (Maniatis, Goodbourn et al. 1987; Kim and Kim 1994). Once phosphorylated, the polymerase is able to leave the PIC and begin synthesizing RNA.

Pol II and the GTFs are required for initiation of the vast majority of protein encoding genes. Therefore, differential regulation of genes is determined by interactions between specific cis–acting elements and trans-acting factors. To put it simply, regulation of individual genes depends on cis-acting elements in the promoter or enhancer regions of the gene along with the presence of activated transcription factors in the nucleus.

Cis-elements reside in the promoter or enhancer of genes, usually in non-coding regions that may be right upstream of the transcription start site (TSS) or several kilobases upstream or downstream from the gene (Maniatis, Goodbourn et al. 1987).

Trans-acting factors, or transcription factors, are DNA-binding proteins that bind these cis-elements leading to repressed or enhanced transcription of the corresponding genes

(Choo and Klug 1997). Transcription factors are grouped into various families based on

shared structural motifs. Some common structures include the basic-helix-loop-helix

(bHLH), the leucine zipper, the zinc finger and the homeobox (Miller, McLachlan et al.

1985; Gehring 1987; Maniatis, Goodbourn et al. 1987; Landschulz, Johnson et al. 1988).

Many transcription factors have been shown to have oncogenic properties. Gene mutations or epigenetic alterations can affect expression of these factors. Gene mutations can also lead to the synthesis of proteins with alterations that disrupt structural elements required for DNA-binding. Due to the important regulatory function of transcription factors, loss-of-function or gain-of-function changes can significantly contribute to malignant transformation. Indeed some of the first oncogenes (Myc and Myb) and tumor suppressor genes (Rb and TP53) identified were transcription factors (Benz 1998).

After initiation there are a number of processes that regulate the steady-state levels of the mRNA. Turnover of mRNAs plays a key role in the overall regulation of gene expression. Accurate recognition of RNA defects must be carefully controlled.

Indeed, RNA molecules with defects in processing, folding, or assembly with proteins are quickly identified and degraded by the surveillance machinery. Mistakes during any of these processes can result in messages containing altered genetic information that could result in translation of misfunctioning proteins. Additionally, an aberrant number of transcripts could result in increased or decreased expression of the proteins they encode.

Again, each of these results can contribute to carcinogenesis.

The surveillance machinery is active immediately following transcription initiation. An m7G cap is added cotranscriptionally to the 5’ end of the nascent RNA.

Failure at this step leads to degradation by 5’ exonuclease and transcription termination

(West, Proudfoot et al. 2008). During elongation, phosphorylation of the C-terminal domain of RNA pol II changes from serine 5 to serine 2. If clusters of Nrd1-Nab3 sites are encountered by Nrd1-Nab3 termination factors prior to serine 2 phosphorylation, transcription is terminated and the RNA is degraded by 3’ exonucleolytic degradation

(Gudipati, Villa et al. 2008). As the transcript grows, introns are removed by splicing machinery leaving the 5’-2’ linked intron lariat. This is debranched by Dbr1 (Chapman and Boeke 1991) and degraded by exonucleases from both ends. Next, cleavage occurs at the 3’ end of the capped and spliced transcript. This event is coupled to the addition of a long poly(A) tail (approximately 250 As in humans) by the poly (A) polymerase

(Houseley and Tollervey 2009). mRNA polyadenylation is highly processive and quickly followed by loading of the poly(A) binding protein (PABP) that enhances mRNA

stability. The uncapped 3’ end of the RNA remains on the elongating polymerase and the

5’ exonuclease Rat1 chases and releases (‘‘torpedo’s") the transcribing polymerase

(West, Proudfoot et al. 2008).

The message is then packaged and exported to the cytoplasm (Rougemaille, Villa et al. 2008). This process can fail for multiple reasons, leading to degradation of the mRNA by 5’ and/or 3’ exonucleases. Defects in assembly of mRNA/protein complexes

(mRNPs) lead to exosome-dependent accumulation of the mRNA in association with the site of transcription, followed by mRNA degradation (Rougemaille, Villa et al. 2008).

Nonsense-mediated decay (NMD) is triggered by components of the assembled mRNP called exon junction complexes (EJC). EJCs are located in an open reading frame upstream of exon-exon junctions to facilitate ribosomal recruitment (Nott, Le Hir et al.

2004). These complexes are displacement by a primary or "pioneer" round of translation

(Ishigaki, Li et al. 2001). Properly assembled mRNPs either couple to nuclear export or undergo this primary round of translation. EJCs located downstream of a nonsense codon or premature codon are not displaced because the ribosome is released from the transcript before reaching it (Chang, Imam et al. 2007). Following transport of the mRNA to the cytosol, the remaining EJCs function as tags for recruitment of UPF1, targeting the RNA for degradation (Isken and Maquat 2008).

In the cytoplasm mRNA undergoes multiple rounds of translation, progressively shortening the poly(A) tail. Following poly(A) tail removal, the mRNA can be decapped by the Dcp1-Dcp2 complex and then subject to either 5’ exonuclease degradation by

Xrn1 or 3’ degradation by the exosome. A major mRNA stability regulator in humans is a

complex including Ccr4 and Caf1, both of which have deadenylase activity (Schwede,

Ellis et al. 2008).

During development, poly(A)-specific ribonulcease (PARN) is the main regulator of deadenylation (Kim and Richter 2006). PARN activity is also important during DNA damage repair and cell-cycle progression. PARN is being study as a potential anti-cancer target due to its involvement in the degradation of several cancer-related genes (Balatsos,

Maragozidis et al. 2012). Recent studies have identified a correlation between enhanced

PARN expression and phosphorylation in acute leukemia. However, functional studies are yet to be completed (Balatsos, Maragozidis et al. 2012; Maragozidis, Karangeli et al.

2012; Meisenberg 1998).

The loss of translational control

The goal of regulatory mechanisms at all levels in the central dogma is often related to regulating protein expression. Therefore it has long been assumed that increased transcription leads to increased mRNA which leads to increased protein expression but it is not always a linear pathway. A recent study of transcriptomes and proteomes in eukaryotic cells demonstrated that protein levels are best explained by translation rates versus transcription rates (Schwanhausser, Busse et al. 2011). In other words, quantifying mRNA expression alone is not sufficient when determining if protein expression levels are altered. Translational control is an important, albeit much over looked, contributor of cancer development. Global control of the proteome, as well as translation of specific classes of mRNAs, can impact major physiological pathways resulting in cancer development and progression. These pathways include cell proliferation/growth, response to cellular stresses such as hypoxia or starvation, and

mitogenic signal stimulation (reviewed in (Dua, Williams et al. 2001; Meric and Hunt

2002; Holcik 2004; Rosenwald 2004)).

Protein synthesis requires 40% of the cells total energy (Meisenberg 1998) so regulation of this process is crucial. As previously discussed, translation initiation is the major regulatory mechanism for protein synthesis. Eukaryotic cells can initiate translation using two mechanisms: cap-dependent translation and IRES-dependent translation. In addition to translation of mRNA, protein levels are also regulated by protein degradation processes.

Regulating protein turnover and its contribution to carcinogenesis are well studied. Proteolysis of cellular proteins is a highly complex, temporally controlled and tightly regulated process. Ubiquitin is an 8 kDa protein of 76 amino-acids named for its ubiquitous presence in cells. Degradation of a protein by the ubiquitin system

(ubiquitination) involves two separate and consecutive steps (Ciechanover 1998). The

first step, conjugation of ubiquitin to a target protein, utilizes three enzymes: E1, E2, and

E3. Ubiquitin is activated in its C-terminal glycine residue by the ubiquitin-activating enzyme, E1. Next, one of several E2 enzymes called ubiquitin-carrier proteins (UBCs)

transfers ubiquitin from E1 to an E3 ligase bound to a specific substrate protein. Once

targeted by a growing chain of ubiquitin molecules, the protein is degraded by the 26S proteasome or sometimes by the lysosomes/vacuole (Ciechanover 1998).

Ubiquitination is a reversible process. Specific de-ubiquitinating enzymes

recognize the isopeptide bond between the C-terminal glycine of one ubiquitin molecule

and the ε-amino group of a lysine of another ubiquitin molecule or of a target protein.

Eukaryotic cells utilize five families of de-ubiquitinating enzymes: the ubiquitin-specific

processing protease (UBP) family, the ubiquitin carboxy-terminal hydrolase (UCH)

family, the ovarian tumor related proteases (OTR) family, the ataxin/Josephin group and the Jab1/MPN domain metalloenzyme)/MPN+ motif (JAMM) proteases (Amerik and

Hochstrasser 2004). De-ubiquitinating enzymes maintain the ubiquitin pool in the cell.

They also perform the important task of proof-reading in which ubiquitin is removed from proteins inappropriately targeted to the proteasome (Amerik and Hochstrasser

2004).

The ubiquitin-proteosome system (UPS) is involved in the regulation of each the processes that can contribute to malignancy of the cell. During mitosis, the Anaphase

Promoting Complex/Cyclosome (APC/C), an E3 ligase, ubiquitinates securin after proper chromosome attachment (Castro, Vigneron et al. 2003). After securin is degraded by the proteasome the sister chromatids can be pulled to the two poles at the end of anaphase

(Matyskiela, Rodrigo-Brenni et al. 2009). UPS regulates the balance between the pro- apoptotic and anti-apoptotic family members which in turn will determine ultimate cell fate after various stimuli (Yang and Yu 2003). Expression of the “guardian of the genome” p53 (for details of p53 function see Aurora A section) is regulated by the UPS through ubiquitination by several different E3 ligases (Leng, Lin et al. 2003).

Angiogenesis is also regulated by the UPS. The α subunit of transcription factor hypoxia inducible factor-1 (HIF-1) is kept suppressed under normoxic conditions by proteasome degradation (Corn 2007). As a result clinical trials using proteasome inhibitors are underway. One therapeutic success is the proteasome inhibitor bortezomib for treating multiple myeloma (Berenson, Yang et al. 2006).

In comparison to protein degradation, translation initiation and its regulatory role

of protein synthesis in cancer is a relatively new field of study. Numerous studies have

associated misregulation of cap-dependent translation initiation with cancer development.

In addition, aberrant expression of the translation factors is seen in a wide selection of

human cancers.

Cap-dependent translation is the main form of translation initiation of eukaryotic

mRNAs. By definition this mechanism requires eIF4E recognition of the 5’ m7G cap

structure. Therefore it is reasonable to propose that any change in eIF4E protein

expression levels or in the ability of eIF4E to form the pre-initiation complex would

result in aberrant expression of a vast majority of cellular proteins. Over-expression of

eIF4E can transform immortalized NIH-3T3 cells (Lazaris-Karatzas, Smith et al. 1992).

Transgenic mouse models have shown that over-expression of eIF4E can enhance the development of lymphomas, sarcomas, and carcinomas (Ruggero, Montanaro et al.

2004). In addition, expression and activation of 4E negative regulators, the 4E-BPs, are important in cancer development. Decreased expression of 4E-BP is seen in advanced prostate cancer with poor prognosis (Coleman, Peter et al. 2009; Graff, Konicek et al.

2009). 4E-BP over-expression is associated with low grade breast cancer and good prognosis (Coleman, Peter et al. 2009; Graff, Konicek et al. 2009) Increased phosphorylation of 4E-BP, which cannot sequester eIF4E and results in enhanced cap- dependent translation, is seen in advanced prostate, breast and ovarian cancers (Noske,

Lindenberg et al. 2008; Coleman, Peter et al. 2009; Graff, Konicek et al. 2009). One current cancer therapeutic, rapamycin, targets cap-dependent translation by downregulating mTOR activity leading to the sequestering of eIF4E by the 4E-BPs.

Other canonical translation factors have also been associated with cancers. eIF4A

is over-expressed in some hepatocellular carcinomas and melanomas (Eberle, Krasagakis

et al. 1997; Shuda, Kondoh et al. 2000). Over-expression of eIF4G has been shown to transform NIH-3T3 cell in the absence of increased eIF4E expression. Increased levels of

4G are found in locally advance breast cancer (LABC), inflammatory breast cancer (IBC)

and squamous lung carcinomas (Comtesse, Keller et al. 2007; Graff, Konicek et al. 2009;

Silvera, Arju et al. 2009). The function and extent of eIF4A or eIF4G overexpression in

cancer is still unknown, therefore further studies are required. Over-expressing a mutant form of the eIF2α subunit that cannot be phosphorylated, which should enhance protein synthesis, does transform NIH3T3 cells and promote tumorigenisis (Koromilas, Roy et al. 1992). Additionally, up-regulation of the eIF2α kinase PKR, which also negatively regulates eIF2 function has tumor suppressor activity experimentally (Barber, Jagus et al.

1995). However, both eIF2α and PKR are often upregulated in certain carcinomas and hematological malignancies (Haines, Ghadge et al. 1993; Terada, Ueyama et al. 2000;

Rosenwald, Hutzler et al. 2001; Rosenwald, Pechet et al. 2001; Wang, Lloyd et al. 2001).

This paradigm is not understood and will required extensive investigation. It has been suggested that factors which counter act translation inhibition by eIF2α phosphorylation may also be upregulated in these same cancer (Kim, Forman et al. 2000).

Ribosomal biogenesis is increased in tumor cells. Ribosomal RNA (rRNA) is

transcribed by RNA polymerase I under regulation of upstream binding factor (UBF).

This factor is regulated by mitogenic signals through MAPK/ERK and PIK3/

AKT/mTOR pathways. These pathways are often activated during transformation and

signaling is increased in some cancers (Stefanovsky, Pelletier et al. 2001; Hay and

Sonenberg 2004; Martin, Soulard et al. 2004). Since almost all rRNA become

incorporated into ribosomes it has been suggest that increased rRNA levels results in

increased ribosome production thereby driving overall levels of protein synthesis.

Changes in expression or activation of the canonical translation factors, their regulators, or ribosomes could potentially affect both cap and IRES mechanisms of translation initiation. However, the effect of these changes can be quite different between the two mechanisms. For example, IRES activity involving eIF2α has been demonstrated.

IRES activity of PDGF2, VEGF, EMCV, and c-MYC is upregulated in the presence of phosphorylated eIF2α even though global protein synthesis is reduced (Gerlitz, Jagus et

al. 2002). Additionally, IRES-specific regulators have been identified. A proteolytically

cleaved form of eIF4G and one of it homologues, DAP5, can selectively upregulate

translation of some IRESes (Henis-Korenblit, Shani et al. 2002). eIF4G is caspase-

cleaved in response to apoptosis. The Apaf-1 and Dap5 IRES elements are upregulated

during apoptosis. Therefore the caspase-cleaved eIF4G can initiate translation of “pro-

death” IRES elements, contributing to the acceleration of cell death.

Up through the late 1990s practically all anti-cancer drugs worked by disrupting

DNA replication. Unfortunately these drugs are also toxic to normal cells, albeit the

rapidly dividing cancer cells are affected to a greater extent. Finding therapies that spare

normal cells and target cancer cells is a common goal for cancer researchers. As scientific

studies uncovered these various molecular mechanisms that contribute to cancer, a wide

variety of therapies against specific molecular targets required for different cellular

processes have been developed. They include growth signal inhibitors that target

signaling pathways involved in cancer cell proliferation such as epidermal growth factor

receptor (EGFR), human epidermal growth factor receptor 2 (HER-2), mammalian target of rapamycin (mTOR), and numerous tyrosine kinases. Other drugs target proteins that regulate gene expression and other cellular functions including, histone deacetylases

(HDACs) and retinoid X receptor. Other treatments target angiogenesis or induce apoptosis. As a result target therapy can be used to treat many different forms of previously untreatable cancers.

Many of the key genes involved in processes that lead to cancer, such as cell proliferation, differentiation, and apoptosis, can be translated in an IRES-dependent manner (see Table 1.1). Additionally, it has been shown that IRES-mediated translation is

upregulated in response to chemotherapeutics and radiation implicating this mechanism

may play a role in drug resistance and reoccurring tumors. As previously discussed,

cellular IRESes can be very different from each other. Although this makes studying

them challenging, these differences could potentially be useful. Translation of certain

IRESes is cell type specific (Creancier, Mercier et al. 2001; Nevins, Harder et al. 2003).

Various IRES elements require specific RNA-binding proteins for recruitment of the translational machinery. It has been hypothesized that distinct pathways may exists that regulate IRES translation by altering expression, function, or activity of IRES-binding proteins (Holcik 2004). Therefore, identifying these pathways and ITAFs is very attractive as it could lead to the discovery of novel drug targets that could be used to treat a variety of tumors and may even help prevent drug resistance.

The Aurora A Oncoprotein

In 1993, the Ipl1 gene was identified in a genetic screen of Saccaromyces cerevisiae for mutations resulting in defective chromosomal segregation (Chan and

Botstein 1993). Two years later a screen of mutations affecting the mitotic spindle poles

in Drosophila melanogaster was reported. This screen identified the first allele for what

was eventually named Aurora because detection of the protein in cells resembled the

aurora borealis (Glover, Leibowitz et al. 1995). By 1998 three Aurora homologues, A, B

and C, were identified in humans (Bischoff, Anderson et al. 1998). These proteins

comprise a family of highly conserved serine/threonine kinases that are essential for

proper regulation of several mitotic events (Fu, Bian et al. 2007). Specifically, Aurora A

(also known as Aurora 2, ARK1, AIRK1, BTAK, STK6, and STK-15) is mainly involved in centrosome function, mitotic entry and spindle assembly (Kollareddy,

Dzubak et al. 2008).

Aurora A kinase and the cell cycle

Regulated expression, localization and activity of the Aurora A kinase is critical for proper cell division (Figure 1.10). In human cells, Aurora A mRNA and protein levels begin to increase during late S phase of the cell cycle. Both Aurora A mRNA and protein levels, as well as Aurora A kinase activity, peak during late G2/M (Shindo, Nakano et al.

1998). Prior to cytokinesis, Aurora A protein is degraded by the Anaphase-Promoting

Complex/Cyclosome (APC/C) During G2, Aurora A is only found at the centrosomes.

However, after nuclear-envelope breakdown (NEBD) Aurora A is located at the spindle poles and bipolar spindles as well. Kinase levels slightly decrease as the cell enters metaphase-anaphase but it is still detected at the centrosomes and spindles. Once anaphase begins Aurora A is also found at the spindle midzone. By the final stage of cytokinesis the kinase is hardly detectable (Kollareddy, Dzubak et al. 2008).

Figure1.10 Aurora A expression, localization and function during the cell cycle Aurora A mRNA and protein (red) levels are detected during late S / early G2 phase of the cell cycle and expression peaks during G2/M. Aurora A contains D-box and A-box domains that are required for protein degradation by the APC/C and is detected in low amounts or not at all after cytokinesis. By G2 phase, Aurora A (red) localizes to pericentriolar material (yellow) and persists throughout mitosis. Additionally, it spreads to the minus ends of the mitotic spindle microtubules and midzone microtubules during mitosis. Aurora A is a key regulator of numerous events during G2/M via activation of numerous substrates that contribute to proper centrosome duplication, mitotic entry, centrosome maturation, chromatin condensation, spindle assembly and bipolar spindle formation (Honda, Mihara et al. 2000; Hannak, Kirkham et al. 2001; Kufer, Sillje et al. 2002; Meraldi, Honda et al. 2002; Dutertre, Cazales et al. 2004; Eyers and Maller 2004; Toji, Yabuta et al. 2004; Cazales, Schmitt et al. 2005; Shao, Wang et al. 2006; Fu, Bian et al. 2007; Mori, Yano et al. 2007; Carmena, Ruchaud et al. 2009).

Full activation of Aurora A depends on interactions between specific protein cofactors. These binding events induce a conformational change in the kinase domain, leading to auto-phosphorylation of the threonine (T) residue T288 in the T-loop of the catalytic domain (Eyers, Erikson et al. 2003). Most importantly, kinase activation at specific cellular locations during mitosis requires timely association with interacting proteins (Carmena, Ruchaud et al. 2009). In the following section I will introduce these interactors and the way in which they modulate the function of Aurora A during different mitotic events.

Aurora A function

The first event dependent on Aurora A activity is remodeling of the pericentriolar material’s (PCM) microtubule nucleating capacity; a process called centrosome maturation (Hannak, Kirkham et al. 2001). During the G2 phase of the cell cycle, cyclin dependent kinase 11 (CDK11) localizes Polo-like kinase 1 (Plk1) to the centrosomes which in turn recruits Aurora A. Centrosomes consist of a pair of centrioles and the PCM which serves as a microtubule organizing center (MTOC). Nucleated centrosomal microtubules interact with the chromosomes to form the mitotic spindle. Transforming acidic coiled coil (TACC) is phosphorylated by Aurora A at the centrosome (Al-Bassam and Chang 2011). As the cell enters mitosis different proteins and other components such as γ-tubulin, kinases and motor proteins are recruited to remodel the PCM, changing the microtubule nucleating capacity (Abe, Ohsugi et al. 2006). The role of Aurora A during centrosome maturation was demonstrated in Aurora A-depleted human cells. In the absence of Aurora A, TACC is not phosphorylated, remodeling of the PCM does not

occur, and cell maturation is inhibited. These results suggest phosphorylation of TACC

by Aurora A kinase is required for remodeling the PCM (Barros, Kinoshita et al. 2005).

TACC is not the only Aurora A substrate involved in centrosome maturation.

Aurora A substrates, large tumor suppressor homolog 2 (LATS2) and nuclear distribution

protein nude-like 1 (NDEL1), have also been shown to contribute to this mitotic event.

LATS2 interacts with Aurora A at the centrosome and is required for accumulation of γ-

tubulin at the PCM. Indeed, knockdown of LATS2 in mammalian cells results in failed

centrosome maturation (Toji, Yabuta et al. 2004). Conversely, degradation of NDEL1

appears to be required for centrosome maturation. Aurora A phosphorlyates NDEL1 and

recruits it to the centrosome for ubiquitlylation and degradation. A phosphomimetic

mutant of NDEL1 has been shown to restore partial centrosome maturation in Aurora A-

depleted cells (Mori, Yano et al. 2007). Other mitotic events including centrosome

separation and mitotic entry are rescued by this NDEL1 phosphomimetic in Aurora A-

depleted cells suggesting Aurora A-dependent degradation of NDEL1 contributes to these

events as well (Carmena, Ruchaud et al. 2009).

Additional evidence has demonstrated Aurora A plays a major role in centrosome

separation. Micro-injectioning HeLa cells in the G2 phase of the cell cycle with affinity-

purified antibodies against Aurora A inhibits separation of centriole pairs after

breakdown of the nuclear envelope (Marumoto, Zhang et al. 2005). This result is due in part to the accumulation of NDEL1. Aurora A plays another role during centrosome separation after NEBD. The Aurora A substrate, kinesin-like motor Eg5, is part of the

EXTAH complex. Formation of this complex is Aurora A-dependent and required for bipolar spindle assembly. EXTAH is comprised of microtubule (MT) stabilizers

(XMAP215), MT bundling proteins (HURD), and MT-crosslinking proteins (Eg5 or

TPX2) (Marumoto, Zhang et al. 2005). Inhibition of either Eg5 or Aurora A leads to the formation of a monopolar spindle (Kapitein, Peterman et al. 2005).

Activated Aurora A kinase at the centrosomes is required for mitotic entry. Once fully activated Aurora A phosphorylates M-phase inducer phosphatase 2 (CDC25B) on

S353 (Dutertre, Cazales et al. 2004; Cazales, Schmitt et al. 2005), leading to the activation of centrosome-associated CyclinB–CDK1 (Hirota, Kunitoku et al. 2003). In

G2, Aurora A in complex with its cofactor Bora activates Polo-like kinase 1 (PLK1) contributing to the final activation of CyclinB–CDK1 (Macurek, Lindqvist et al. 2008).

PLK1 promotes degradation of Wee1, the negative regulator of CDK1 (van Vugt, Bras et al. 2004) allowing for entry to mitosis.

The activation of the Aurora A kinase is important for each mitotic event it regulates. Ajuba, a LIM protein, is both a substrate and activator of Aurora A. It interacts with Aurora A in mitotic cells and phosphorylation of both proteins occurs

(transactivation). In vitro studies revealed that Ajuba induces auto-phosphorylation of

Aurora A. Depletion of Ajuba prevents Aurora A activation at the centrosomes in late G2 and inhibits mitotic entry (Hirota, Kunitoku et al. 2003; Marumoto, Honda et al. 2003).

The most studied Aurora A activator is targeting protein for Xenopus kinesin-like protein 2 (TPX2). This cofactor has a dual role in Aurora A activation. TPX2 is a microtubule-associated protein (MAP) that targets the kinase to the mitotic spindle (but not the centrosome) and activates it (Wittmann, Wilm et al. 2000; Kufer, Sillje et al.

2002). Its N-terminus binds Aurora A, inducing a conformational change that facilitates auto-phosphorylation of T288 (Bayliss, Sardon et al. 2003; Eyers, Erikson et al. 2003).

Additionally, bound TPX2 shields T288 from dephosphorylation by protein phosphatase

1 (PP1) as the cell enters mitosis (Bayliss, Sardon et al. 2003; Eyers, Erikson et al. 2003).

The Aurora A oncogenic signaling pathway

Since 1998, several reports associating Aurora A over-expression with

malignancies have been published. The list includes breast, colorectal, bladder, pancreatic, gastric, ovarian and esophageal cancers (Zabaleta 2012; Bischoff, Anderson et al. 1998; Tanner, Grenman et al. 2000; Tanaka, Ueda et al. 2002; Gritsko, Coppola et al. 2003; Li, Zhu et al. 2003; Tong, Zhong et al. 2004; Hata, Furukawa et al. 2005;

Comperat, Camparo et al. 2007; Lassmann, Shen et al. 2007; Nishida, Nagasaka et al.

2007). To determine if increased Aurora A expression contributes to tumorigenesis both cell and animal models were analyzed. Over-expression of Aurora A causes centrosome amplification both in cell cultures and in a rat mammary model (Goepfert, Adigun et al.

2002; Meraldi, Honda et al. 2002; Anand, Penrhyn-Lowe et al. 2003). Cells over- expressing Aurora A also abrogate the mitotic spindle checkpoint and enter anaphase even though spindle formation is abnormal (Anand, Penrhyn-Lowe et al. 2003).

Interestingly, over-expression of a kinase-dead mutant form of Aurora A also resulted in genetic instability (Dutertre, Descamps et al. 2002). However only over-expressing a kinase active Aurora A could transforms NIH 3T3 cells and Rat1 fibroblasts in vitro.

When these cells were injected into nude mice, they grew into tumors. Additionally, mammary tumors formed in transgenic mice over-expressing Aurora A (Wang, Zhou et al. 2006; Mountzios, Terpos et al. 2008).

Overall, these in vitro and in vivo studies show Aurora A induces tumorigenesis via events leading to genomic instability. They also demonstrate that deregulation of a

single mitotic regulator can lead to tumorigenesis (Fu, Bian et al. 2007). Understanding how genomic instability resulting from Aurora A over-expression leads to tumorigenesis versus cell death is still not clear. Recent studies focusing on signaling crosstalk between

Aurora A and other proteins have identified several candidates that may contribute to transformation of Aurora A over-expressing cells.

One candidate is the tumor suppressor breast cancer type 1 susceptibility protein

BRCA1. BRCA1 is part of a protein complex known as the BRCA1-associated genome surveillance complex (BASC) that repairs double-strand DNA breaks (Wang, Cortez et al. 2000). Mutations of the BRCA1 or BRCA2 genes greatly increase a woman’s risk for breast and ovarian cancer. Researchers have identified hundreds of mutations in the

BRCA1 gene, many of which are associated with the hereditary breast-ovarian cancer syndrome (Mazoyer 2005).

BRCA1, like Aurora A, is localized to the centrosomes and binds γ-tubulin (Hsu and White 1998; Okada and Ouchi 2003; Sankaran, Crone et al. 2007). BRCA1 has also been shown to directly interact with Aurora A. Serine 308 of the BRCA1 protein has been identified as an Aurora A phosphorylation site (Ouchi, Fujiuchi et al. 2004).

Expressing a phospho-deficient form of BCRA1 in BRCA1-mutated mouse embryonic fibroblasts (MEFs) led to cell arrest at G2, implicating phosphorylation of BRCA1 at

S308 is required for deactivating the G2 checkpoint and transitioning into mitosis.

Similarly, it was shown that ionizing radiation eradicated phosphorylation of BRCA1 by

Aurora A and again the cells arrest at the G2 phase. Together, these results suggest that the unphosphorylated form of BCRA1 is required for continued activation of the G2/M checkpoint. One hypothesis is increased phosphorylation of BRCA1 in cells over-

77 expressing Aurora A kinase would result in the cells progressing unchecked through the

G2/M checkpoint and thereby lead to genetic instability. However, U2OS cells (an osteosarcoma cell line) exogenously over-expressing Aurora A do not show an increase of BRCA1 phosphorylation at S308. This lack of phosphorylation of BRCA1 could be due to substrate specificity of Aurora A under different physiological conditions (Saeki,

Ouchi et al. 2009).

A potential regulator of Aurora A expression that may also contribute to full transformation of Aurora A over-expressing cells is checkpoint with fork-headed- associated and ring fingers (CHFR). This mitotic checkpoint protein is absent in 20-50% of tumors and primary cell lines. CHFR is an ubiquitin ligase and Aurora A is a speculated CHFR target. The C-terminal cysteine rich region of CHRF does interact with the N-terminus of Aurora A (Saeki, Ouchi et al. 2009). Also Aurora A protein levels were high in CHFR-null MEFS as well as in MCF10A cells depleted of CHRF via siRNA

(Scolnick and Halazonetis 2000; Privette, Weier et al. 2008). Cells over-expressing

CHFR did not show changes in either protein expression levels or localization of Aurora

A. However inducing the CHFR-mediated mitotic delay in these same cells using nocodazole did result in the accumulation of unphosphorylated T288 Aurora A

(Summers, Bothos et al. 2005). This is an interesting result since over-expression of a kinase-dead mutant of Aurora A can lead to genomic instability. However, further study is required to determine if differential expression of CHFR plays a role during transformation of Aurora A over-expressing cells.

Another protein affected by enhanced Aurora A activity that potentially contributes to cell transformation of Aurora A over-expressing cells is the well studied

p53. This tumor suppressor is encoded by the TP53 gene and has been termed the

“guardian of the genome” due to its important roles during DNA damage and ribosomal

stress (Pei, Zhang et al. 2012). When activated p53 determines whether to induce cell

cycle arrest or signal apoptosis (Miliani de Marval and Zhang 2011). The selectivity of p53 for specific transcriptional targets requires precise control of p53 activity and involves the coordination of numerous mechanisms (Kruse and Gu 2009; Vousden and

Prives 2009). Mutation of the TP53 gene resulting in aberrant function and/or expression of the p53 protein occurs at a high frequency in many human tumors.

The association between Aurora A and p53 is rather complex. First p53 can suppress centrosome amplification resulting from over-expression of Aurora A

(Katayama, Sasai et al. 2004). In addition, p53 can interact with Aurora A in a

transactiviation-independent manner which inhibits its oncogenic activity (Chen, Chang

et al. 2002). Conversely, over-expression of Aurora A can lead to p53 degradation

thereby promoting cellular transformation. Aurora A in cancer cells has been shown to

phosphorylate p53 at S315 which facilitates ubiquination and degradation of p53 by

Mdm2 (Katayama, Sasai et al. 2004). There is a second Aurora A phosphorylation site on

the p53 protein (S215) that eliminates p53 DNA-binding potential when phosphorylated.

This results in the downregulation of two p53 target genes–tumor suppressors p21 and

PTEN (Liu, Kaneko et al. 2004). p53 also regulates transcription of GADD45a, a strong

negative regulator of Aurora A kinase activity (Shao, Wang et al. 2006). In addition, p53

colocalizes with Aurora A at the centrosome, where it may inhibit the kinase directly.

TPX2 binding shields the Aurora A T-loop from p53 inhibition (Eyers and Maller 2004).

There is evidence that small-molecule inhibitors of Aurora A kinase activity are more

affective in the presence of p53 (Huck, Zhang et al. 2010; Nair, Ho et al. 2012;

Gizatullin, Yao et al. 2006). However a role for p53 in Aurora A over-expressing

transformation has yet to be determined.

The last potential contributor to Aurora A over-expressing cellular transformation

is mammalian target of rapamycin (mTOR). mTOR is a serine/threonine kinase that is

involved in numerous cellular processes. Signaling via growth factor or hormones leads

to activated mTOR. Phosphoryated mTOR can form two separate complexes. The first,

and better studied, complex is mTORC1 which is composed of mTOR, mLST8, raptor

and PRAS40. This complex is sensitive to rapamycin. It functions in translation,

ribosome biogenesis, transcription, autophagy and hypoxic adaption (Chiang and

Abraham 2005). The second complex mTORC2 includes mTOR and mLST8 along with

unique factors rictor, mSIN1, and PRR5. This less studied complex phosphorylates AKT

on S473 and also regulates actin cytoskeleton through an unknown mechanism that

involves small GTPases Rho and Rac. It has also been shown to phosphorylate PKC and

SGK1 which has implications in controlling cell size (Jacinto, Facchinetti et al. 2006).

An interesting study shows that constitutive phosphorylation of mTOR S2448 and

AKT S473 is present in mammary tumors of MMTV-Aurora A transgenic mice (Wang,

Zhou et al. 2006). The enhanced phosphorylation of mTOR and AKT in Aurora A

transformed cells indicates the potential regulation of both mTORC1 and mTORC2 by

Aurora A. Indeed, mTOR inhibitors can eliminate Aurora A transformation phenotypes

(Taga, Hirooka et al. 2009). However, a large number of passages are required before

stable transfectants over-expressing Aurora A show increased mTOR and AKT

phosphorylation.

Together, these studies strongly suggest that additional events must occur before

Aurora A over-expressing cells become tumorigenic. One study of p53 wild-type (WT)

U2OS transfectants, stably over-expressing Aurora A, shows that an increase of p53

levels and activity occurs during early passages (p10) compared to controls. (Taga,

Hirooka et al. 2009). Phosphatase and tensin homolog (PTEN), a p53 regulator and tumor

suppressor, was also upregulated in those p10 cells. However by p20 both p53 and PTEN

protein expression levels were decreased. Interestingly, enhanced p-S473 of AKT was seen in p20 and p40 cells but not p10 cells. It was further shown this increase of AKT phosphorylation was mTOR-dependent. Finally, this group demonstrated that cell proliferation between p10 and p40 were similar and increased compared to controls.

Additionally p10 cells were capable of forming small colonies in soft agar although p40

cells formed larger colonies. They concluded p53 acts as a gate keeper in Aurora A over-

expressing cells as demonstrated by activation of pro-apoptotic signaling. However,

Aurora A over-expressing cells survive. The results agree with the latency of tumor

development shown earlier by this group in a MMTV-Aurora-A mice model (Harrington,

Bebbington et al. 2004).

Unfortunately this cell line is not the best choice to conclude if increased Aurora

A activity was responsible for the cells overcoming p53 induced pro-apoptotic signaling.

These cells are already cancerous and chromosomally highly unstable in a p53 wild-type

background thus they must already possess a mechanism to overcome p53 signaling.

Still, this study does demonstrate an increase of mTOR/AKT signaling after 20 passages

of over-expressing Aurora A, even in the presence of WT p53, suggesting that this

pathway may be involved in Aurora A cellular transformation. It would be beneficial to

repeat this experiment in a normal, primary epithelial line to determine if these findings

result from enhanced Aurora A protein expression alone.

Crosstalk with other signaling pathways has been reported. Aurora A has been shown to enhance activation of the glycogen synthase kinase (GSK)-3β and the β-

catenin/TCF complex in gastric tumors (Dar, Belkhiri et al. 2009). Aurora A has been

found to be a downstream target of mitogen-activated protein kinase 1/ERK2 in

pancreatic cancer (Furukawa, Kanai et al. 2006). In both ovarian and breast epithelial

cells, over-expression of Aurora A induces human telomerase reverse transcriptase

(hTERT) expression which inhibits cellular aging and promotes cell survival in cancer.

One hypothesis is that enhanced telomerase activity results from upregulation of c-myc

by enhanced Aurora A activity, resulting in immortalization (Yang, Ou et al. 2004). In

addition to immortalization, Aurora A is thought to contribute to invasiveness and

metastasis. For example, activation of RalA in an Aurora A stable transfectants

augmented collagen I-induced cell migration and anchorage-independence (Wu, Chen et al. 2005).

As a result of these findings, clinical trials with anti-cancer drugs targeting Aurora

A kinase activity are underway. However, there is still the issue of targeting Aurora A function specifically to cancer cells. In order to identify a way to kill cancer cells yet spare normal cells, further studies of both Aurora A activity as well as Aurora A expression is warranted. In the next section I will discuss current methods being used to target Aurora A activity in cancer cells along with novel ideas for targeting Aurora A expression.

Targeting Aurora A in cancer cells

Progress has been made in understanding Aurora A’s function in cancer

development. Given its critical role in mitosis, many small-molecule inhibitors targeting

Aurora A kinase activity are already in development and are involved in clinical trials

(Mountzios, Terpos et al. 2008; Kitzen, de Jonge et al. 2010). Unfortunately this method

of anticancer treatment has to overcome major caveats including both drug delivery and

target specificity.

Many kinases being studied as potential anticancer drug targets have overlapping

function and structures. This is true for the Aurora kinases. Aurora C can essentially

replace Aurora B function when Aurora B activity is inhibited. Structure of the active site

of the three Auroras is very similar since it resides in the highly conserved region of the

proteins. As a result, the first small-molecules developed to target Aurora A were pan-

kinase inhibitors (Keen and Taylor 2004). It has been determined these drugs, including

ZM447439, Hesperadin and VX-680, lead to aberrant mitosis, but cell death is caused by

activation of a p53-dependent post-mitotic checkpoint induced ‘pseudo G1’ cell-cycle

arrest (Kitzen, de Jonge et al. 2010). In other words, treating cancer with these inhibitors

would require active p53. Unfortunately p53 activity is often downregulated in many tumor types.

A second issue for targeting Aurora A kinase activity is chromosomal instability

as a result of over-expressing Aurora A can lead to misregulation of additional proteins

that contribute to tumorigenesis. Therefore combination therapy is most likely necessary.

This idea has been demonstrated in a cell culture studies. Inhibiting Aurora A and mTOR

kinase activity simultaneously increased apoptosis in cells compared to inhibiting activity

of each kinase independently (Taga, Hirooka et al. 2009).

One drawback to combination therapy is that multiple small-molecule inhibitors

may inhibit the activity of additional kinases (Lee, Frolov et al. 2006) increasing the risk

of toxicity. Despite the challenges, several small-molecule Aurora A inhibitors have been

created. Trials involving these drugs have yet to been completed (Kitzen, de Jonge et al.

2010).

In the meantime, alternative approaches to selectively target the Aurora A kinase

are being considered. For instance, knocking down Aurora A expression using RNA

interference (RNAi) inhibits cell proliferation and tumorigenicity (Hata, Furukawa et al.

2005). One possible advantage to this approach is that tumor cells may be more

susceptible than normal dividing cells to undergo apoptosis in response to the decreased

expression versus inhibited activation of Aurora A. Also, since combination therapy is most likely required, targeting Aurora A expression versus kinase activity may prove to be less toxic to non-cancerous cells. Another advantage to targeting expression instead of activity is this method would eliminate any unknown function of unphosphorylated

Aurora A protein. Indeed, over-expressing a kinase-dead mutant (T288A) Aurora A protein can cause chromosomal instability (Dutertre, Descamps et al. 2002) In addition, recent data has shown that unphosphorylated Aurora A can still be catalytically active.

When unphosphorylated Aurora A is bound to the mitotic spindle by TPX2, Aurora A catalytic active can increase 15-fold. Therefore, the phosphorylation state of Aurora A is an inaccurate indicator for its activity (Dodson and Bayliss 2012) and targeting T288 of the T loop may not eliminate all Aurora A function.

Questions: overview of study

The events that contribute to enhanced Aurora A expression during early cancer development are still unclear. Identifying these mechanisms would contribute to our

knowledge of carcinogenesis, lead to novel methods to target Aurora A over-expression

in tumors, and reveal additional targets that could be used in combination with Aurora A inhibition to treat tumors.

Prior to this study, various mechanisms leading to the over-expression of the

Aurora A kinase have been proposed. The Aurora A gene is located on the 20q13 chromosomal region. This region is often amplified in tumors resulting in increased

Aurora A mRNA and protein expression (Tanner, Tirkkonen et al. 1994; Tanner,

Tirkkonen et al. 1995; Bischoff, Anderson et al. 1998; Zhou, Kuang et al. 1998; Tanner,

Grenman et al. 2000). However, there are many examples where Aurora A mRNA levels are increased without amplification, suggesting changes in transcription rate and/or mRNA stability (Zhou, Kuang et al. 1998; Sakakura, Hagiwara et al. 2001; Jeng, Peng et al. 2004; Tong, Zhong et al. 2004). Finally, translational regulation such as the rate of mRNA translation and protein degradation can influence protein levels regardless of the mRNA level, indicating the involvement of post-transcriptional mechanisms (Lai, Tseng et al. 2010; Taga, Hirooka et al. 2009).

Utilizing a set of tissue culture cells, including two normal lines with finite lifespans (lung fibroblast WI-38 cells and human mammary epithelial cells (HMECs)),

two immortalized but non-tumorigenic breast epithelial cell lines (MCF10A and

MCF12A cells), and two tumorigenic epithelial cell lines from breast (MCF-7) and cervix

(HeLa S3), I identified a subset that over-expressed Aurora A protein solely by increased

85 translation initiation. I went on to discover the 5’ leader of the Aurora A mRNA contained IRES activity. Increased internal translation initiation of this leader correlated with increased Aurora A protein expression. My goals for this study were to answer the following questions:

• Does cap-dependent and/or IRES-dependent translation initiation regulate

expression of the Aurora A mRNA in normal cells? in cancer cells?

• Is the IRES active during the G2/M phase of the cell cycle when Aurora A

expression is known to increase despite inhibited cap-dependent translation?

• What IRES cis-elements are present in the 5’ leader of the Aurora A mRNA?

• What ITAFs regulate these elements?

• What signaling pathways control internal initiation of the Aurora A mRNA?

• Does aberrant IRES activity contribute to Aurora A overexpression during

immortalization?

• Does aberrant IRES activity play a role in other stages of cancer development?

• And lastly: could targeting Aurora A IRES activity serve as an anti-cancer

treatment?

CHAPTER II

MATERIALS AND METHODS

Constructs and Cloning

The FMR1, Aurora A and β-globin 5’ leaders (GenBank accession numbers:

FMR1, NM_001185081.1; Aurora A, XM_114165; β-globin, V00497) were PCR amplified from a human brain cDNA library (Clontech) and inserted into the dual luciferase vector - pRF (Stoneley, Paulin et al. 1998; Stoneley, Subkhankulova et al.

2000) (a generous gift from Dr. Anne Willis, University of Leicester) with EcoRI and

NcoI restriction endonuclease sites. The promoterless construct was created by digesting the dicistronic pRF (RP, I refer to the construct as RP for Renilla and Photinus instead of

Firefly) construct with SmaI and EcoRV and religating the construct.

The dicistronic construct for in vitro transcription was created by digesting the RP vector with EcoRV and BamHI releasing the Renilla and Photinus gene and the SV40 3’- untranslated region (3’-UTR). The two luciferase genes were inserted into the multiple cloning site of the SK+ Bluescript vector (Stratagene) downstream of the T7 promoter.

The monocistronic construct for in vitro transcription was created by digesting the RP vector with EcoRI and BamHI. The digest released the 5’ leader, the Photinus luciferase gene and the SV40 3’-UTR, which were inserted into the multiple cloning site of the SK+

Bluescript vector (Stratagene) downstream of a T7 promoter. The monocistronic vector for the FMR1 ex vivo experiments was created by digesting the RP vector with EcoRI and BamHI. The digest released the 5’ leader, the Photinus luciferase gene, and the SV40

3’ UTR, which were cloned into the pGL3 vector (Promega).

The 4E-BP1 double mutant and control expression plasmids were generously

provided by Dr. Nahum Sonenberg (McGill University, Montreal). The Δ5 4E-BP1

mutant was generously provided by Dr. Davide Ruggero (University of California, San

Franciso).

Serial truncations of the FMR1 5’leader were produced by PCR amplification with 5’ and 3’ primers containing EcoRI and NcoI endonuclease restriction sites, respectively. Deletion of the CGG repeats was accomplished by amplifying the region 3’ to the repeats in the FMR1 5’ leader and inserting it into the pRF construct with EcoRI and NcoI restriction sites on the 5’ and 3’ end respectively. The 5’ leader upstream of the

CGG repeats was amplified and inserted upstream of the 3’ FMR1 5’ leader using EcoRI restriction sites.

The Aurora A 5’ UTR splice variants were by PCR amplification (with the 5’ end primer targeting the downstream transcription start site and the 3’ primer targeting the

ORF just downstream of the start codon) from cDNA libraries created from WI-38,

HMEC, MCF10A, MCF12A ,MCF-7, and HeLa S3 cell lines. PCR products were cloned into sequencing vectors using TOPO® TA Cloning® Kit (Invitrogen). These vectors were transformed in competent cells created with Z-CompetentTM E. coli

Transformation Kit & Buffer Set (Zymo Research) for amplification. Plasmid DNA was isolated using PureLink® Quick Plasmid Miniprep Kit (Invitrogen) or Nucleospin miniprep kit (Clontech) and submitted for sequencing. Verified leaders were PCR amplified from the Topo TA vectors with 5’ and 3’ primers containing EcoRI and NcoI endonuclease restriction sites and ligated into the monocistronic construct for in vitro transcription.

In Vitro Transcription

The dicistronic and monocistronic SK+ Bluescript vectors were linearized with

BamHI and used as templates for in vitro transcription. The linearized plasmid was purified by running digests on a 1% agarose gel, gel excising the linearized plasmid, and gel extracting using Zymoclean™ Gel DNA Recovery Kit (Zymo Research). 1µg of linearized plasmid DNA was transcribed at 37°C for 3hrs. For the in vitro translation assay, monocistronic templates were transcribed using mMessage mMachine® T7 Ultra

(Ambion) producing capped mRNA. For the RNA transfection assays, dicistronic and monocistronic templates were transcribed using MEGAScript® T7 (Ambion) producing either ApppG capped (New England Biolabs) or uncapped RNA. Cap priming of messages with an ApppG cap was done by the addition of 3µL 40mM G(5')ppp(5')A

RNA cap structure analog and 2µL 15mM GTP to transcriptions. Transcriptions were then treated with 1µL DNase (2U/µL) for 15 mins at 37°C. mRNA was phenol/chloroform purified, isopropanol precipitated, and resuspended in nuclease free water. M7GpppG caps were added using Script Cap™ m7G capping system

(Cellscript.Inc) and transcripts were poly (A) tailed using Poly (A) Polymerase tailing kit

(Epicentre) per manufacturer’s instructions. mRNA was phenol/chloroform purified, isopropanol precipitated, and resuspended in nuclease free water. ). mRNA quality was verified by running 1µg of mRNA on a Reliant® Precast RNA gel (LONZA) for 1.5hrs and stained with SYBR® gold (Invitrogen). RNA was stored at -80°C.

In vitro Translation

An aliquot of 0.5 mg of in vitro transcribed mRNA, cap analog (Ambion) and 1.6 nM methionine was added to rabbit reticulocyte lysate (Speed Read, Novagen) that was

thawed on ice and incubated for 1 h at 30˚C. The sample was subsequently assayed for

Photinus and Renilla luciferase activity.

Cell Culture Maintenance

C6 cells were obtained from ATCC and cultured in DMEM, 10% fetal bovine

serum and 200 mM L-glutamine. WI-38 (CCL-75) was obtained by American Type

Culture Collection (ATCC, Manassas, VA) and cultured in MEM plus 10% FBS and 5%

Pen/Strep. MCF-7 (HTB-22), HeLa (CCL-2) and HeLa S3 (CCL-2.2) were also obtained by ATCC and cultured in DMEM plus 10% FBS and 5% Pen/Strep. HMEC (A10565) was obtained by Invitrogen and cultured in the recommend media. HMEC-t was generously provided by James Degregori (University of Colorado Anschutz Medical

Center) and culture in the HMEC media. MCF10A, MCF12A, and the 21 T series were

generously provided by Heide Ford (University of Colorado Anschutz Medical Center).

MCF10A and MCF12A were cultured as previously described (Ford 1998). 21PT,

21NT, 21 MT2, and were cultured as previously described (Schedin 2004). All cells were

cultured at 37˚C, 5% CO2.

DNA and RNA Luciferase Assays

Cells were transfected with 2 ug of DNA using Fugene transfection reagent

(Roche) or 4 ug of mRNA using the TransMessenger RNA transfection reagent (Qiagen)

according to the manufacturer’s directions. After 24 hr (DNA transfections) or after 4 or

7 hours (RNA transfections), the cells were lysed with 500 µl of lysis buffer (Promega).

Forty microliters of the supernatant were used for the luciferase assays using the Dual-

Luciferase Reporter Assay (DLA) System and analyzed in a Luminoskan luminometer.

Simulated Neuronal Activity Treatments

Cells were treated with polyinosinic:polycytidylic acid, amiloride, and potassium

chloride (KCL) obtained from Sigma. 1.25 x 105 (amiloride) or 2.5 x 105 (KCL and poly

I:C) C6 cells were plate in 6-well dishes and grown overnight (O/N) at 37˚C, 5% CO2.

For amiloride treatment: Cells were treated with 500 µM of amiloride for 24

hours. Cells were transfect with mRNA at hour 17. Cells were harvested 7 hour later in

cell lysis buffer (Promega) with protease (Roche) and phosphatase inhibitors (Pierce) and

analyzed via western blot or DLA.

For KCL treatment: 50 mM of KCL was added to cells for 30 or 150 minutes

prior to RNA transfection. Cells were washed 1X with PBS and transfected with mRNA.

Cells were harvested 7 hour later in cell lysis buffer (Promega) with protease (Roche) and

phosphatase inhibitors (Pierce) and analyzed via western blot or DLA.

For poly I:C treatment: Cells were transfected with mRNA. 30 minutes after

transfection, 500 µg/ml of poly I:C was added. Cells were harvested 7 hour later in cell

lysis buffer (Promega) with protease (Roche) and phosphatase inhibitors (Pierce) and

analyzed via western blot or DLA.

Cap-dependent Inhibition Assays

In experiments using a hypophosphorylated form of 4E-BP1 (Δ2 containing T37A

/ T46A mutations or Δ5 containing T37A / T46A / S65A / T70A / S101A) plasmids

expressing this protein or the parent vector (both based on pACTAG-2) or control vector

(Paltag) were co-transfected with the monocistronic constructs described above, using a

8-fold molar excess of the 4E-BP1 or control expression constructs with Fugene® 6 transfection reagent (Roche). After 48 hrs, expression was analyzed via western blotting.

The 4E-BP1 double mutant and control expression plasmids were generously provided by

Dr. Nahum Sonenberg (McGill University, Montreal). The Δ5 4E-BP1 mutant was

generously provided by Dr. Davide Ruggero (University of California, San Franciso).

Nonsense siRNA of 10 mM (Dharmacon, D-001206-1O-20) or human eIF4E siRNA (Dharmacon, M-003884-03)) were incubated in 35-mm plate wells with 12 µl of

INTERFERin® transfection reagent (PolyPlus-Transfection) at 37˚C for 10 min. C6 cells or HeLa cells were plated at 1.0x106 in wells already containing siRNA complexes and

serum-free growth media. Complete growth media was then added to a final volume of 2

ml. After 72 hrs, cells were harvested in cell lysis buffer (Promega) with protease

(Roche) and phosphatase inhibitors (Pierce) and analyzed via western blotting.

1 x105 C6 cells were plates in a 6 well dish and grown overnight (O/N) at 37˚C,

5% CO2. The next day 20uM of rapamycin was added to cells. 24 hours later cells were

harvested in cell lysis buffer (Promega) with protease (Roche) and phosphatase inhibitors

(Pierce) and analyzed via western blotting.

Western Blot Analysis

Cells were harvested in cell lysis buffer (Promega) with protease (Roche) and

phosphatase inhibitors (Pierce). Cells were centrifuged for 20 minutes at maximum speed

4°C to remove cell debris. The lysate was removed to a fresh tube and stored at -80°C.

5X SDS loading dye (100% glycerol, 20% SDS, 1M Tris pH 6.8, DTT,

bromophenolblue) were added to aliquoted lysate samples. Samples are boiled for 5-10

mins. Samples were loaded onto a 10% or 12% SDS-PAGE gel, and run in 1X Running

buffer (Tris Glycine) at 200 Volts for 35-45 mins. The transfer apparatus was assembled

as follows: black side of sandwich, sponge, 3 filter paper squares, gel, nitrocellulose, 3

filter paper squares, sponge, clear side of sandwich. The transfer sandwich was placed in

the apparatus with the black to black. 1X transfer buffer (Tris Glycine and 100% MeOH)

was added up to the top of the apparatus. The gel was transferred for 35 mins at 400

mAMPS. The blot was blocked with 5% milk in 1X TBST (blocking solution) for 1hr at

room temperature. The blot was washed 2X with ddH20. The blot was exposed to 1°

antibody diluted in TBST (of PBS containing 0.1% Tween 20) for 1hr at RT or overnight

at 4°C. The blot was washed with 1X TBST for 5 minutes and repeated 4X. The blot was

exposed to 2° antibody diluted in or TBST for 30 minute (anti-rabbit) 1hr (anti-mouse) at

RT. The blot was washed 4X for 5 minutes in 1X TBST. The blot was rinsed in ddH20

2X for 3mins. Immunoreactive bands were detected using Amersham® ECL plus (GE

Healthcare-FMR1 study) or ECL-plus chemiluminescent detection reagent (Promega-

Aurora A study). The blot was detected with either x-ray film or STORM imager and

quantified using Image Quant software.

Table 2.1 Primary and secondary antibodies Antibodies Dilution Source FMRP 1:200 Hybridoma Bank phosphorylated p70 S6 1:1000 (49D7) Cell Signaling kinase Gapdh 1:2500 (ab9485) Abcam-FMR1 study Jun B p160 1:1000 (3755S) Cell Signaling Aurora A 1µg/ml (35C1) Calbiochem eEF2K 1:1000 (3692) Cell Signaling eIF4E 1:1000 (610269) BD Transduction Gapdh 1:200 (FL-335) Santa Cruz Biotechnology- Aurora A study Phosph-4E-BP1 1:1000 Cell Signaling (Thr37/46) HRP-conjugated anti- 1:2500 – 1:10,000 Promega mouse

Polysome Analysis

Cells were treated with cycloheximide (50 ng/mL) for thirty minutes, then

harvested on ice in PBS containing 50ng/mL of cycloheximide and finally lysed with 400

µL of 100 mM KCL, 50 mM Tris0Cl, 1.5 mM MgCl2, 1mM DTT, 1.5% NP-40, protease

inhibitors (Roche), 100 µg/mL cycloheximide and 100 U RNasin® plus RNase inhibitor

(Promega). Then 300 µL of lysate was loaded on a 20–60% sucrose gradient created

using a BIOCOMP Gradient Station, and centrifuged at 39,000 rpm for 2 hrs at 4 °C,

using a SW40Ti rotor (Beckman Coulter). The gradient was fractionated. Total RNA was

extracted from each fraction by adding 750 µl of TRIzol® Reagent (Sigma) per 250ul of

the fraction followed by PureLink™ RNA Mini Kit (Invitrogen ) and analyzed by qRT-

PCR.

RNA Extraction/qRT-PCR

Total RNA was extracted using TRIzol® Reagent (Sigma) followed by

PureLink™ RNA Mini Kit (Invitrogen). cDNA libraries were synthesized using iScript™ cDNA Synthesis Kit (Bio-Rad), including a (-)RT control. For primer pairs see Appendix

A. qRT-PCR was performed using a Roche Lightcycler® 480 with either LightCycler®

480 SYBR Green I Master (Roche) or SsoAdvanced™ SYBR® Green Supermix (Bio-

Rad) per manufacturer’s instructions.

siRNA Human Kinase/ Phosphotase Library Screen (Invitrogen)

The following protocol and tables were for use with HeLa S3 cells in 96 well plates. Adjust volumes accordingly for different size plates and/or cell lines.

Table 2.2 Reverse transfection with INTERFER-in Transfection Agent 3 µL of 1:6 dilution of INTERFER- in = 0.5 µL of 100% INTEREFERin siRNA 0.5pmol = 5nM = 2 µL of 500nM Stock Cell Density 6000 cells/well Volume of medium w/o serum for 50 µL complex formation Volume of complete medium on cells 150 µL (150ul of 40cells/µl = 6000 cells) Final Volume per Well 200 µL

Forty-five µL of serum free medium was added to a clear 96 well, white walled plate using a repeater with a 0.5 ml sterile tip. 2 µL of 500 nM stock siRNA was transfered from the daughter plate to each well using 1-10 µL multichannel pipetter and mixed by pipetting up and down five times. 3 µL of diluted INTERFER-in (.5 µL

INTERFER-in plus 2.50 µL of NFW per well) was added to serum free medium using a repeater with a 0.1mL sterile tip, being careful to avoid touching the tip to side of well and mixed promptly by agitating the plate on an orbital rotator 5 minute. The plates were incubated for 15 minutes at room temperature to allow transfection complexes to form without exceeding 30 minutes. Cells were added to each well (150 µL at 40 cells/ µL) in complete culture medium onto the siRNA/INTERFER-in complexes solution using a repeater with a 5 mL tip, making certain the tip is perfectly vertical. The plate should not be rocked after adding the cells. The final volume per well was 200µL and the siRNA concentration was 5 nM. The plate was incubated at 37°C for 48 hours prior to RNA transfection.

Table 2.3 RNA transfection with TransMessenger Transfection Agent 0.5µL of TransMessenger Additional Reagent 0.125 µL of enhancer RNA 62.5ng of RNA* Volume of medium w/o serum for 12.5µL complex formation Volume of medium w/o serum on cells 50µL Final Volume per well 62.5µL

The medium was aspirated and 50 µL of serum free medium was added to each

well using a repeater with a 5 ml tip. A master mix of RNA/lipid complex was prepared

for the entire plate by adding the RNA and enhancer to the buffer, vortexing the tube for

10 seconds, collecting the mix by a quick spin, and incubating for 5 minutes at RT. The

TransMessenger lipids were added and mixed by vortexing the tube for 10 seconds,

collecting the mix by a quick spin, and incubating for 10 minutes at RT. 12.5µL of the

RNA/lipid complexes were added to each well with a 20 µL pipette and incubate at 37̊ C

for 4 hours. The medium was aspirated. 50 µL of Lysis Buffer was added to each well

using the repeater with a 5 ml tip. The plate was rocked at RT for 15 minutes. 40 µl of the lysate were transferred to an opaque white 96 well plate using the 10-100 µL multichannel pipetter and luciferase activity was measured. Filter tips are NOT necessary for this step.

The RNA used for entire screen was in vitro transcribed, pooled, aliquoted

(enough RNA for an entire 96 well plate) and stored at -80 °C. Aliquots were use only once.

EGF induction

On the first day 2.5 x105 cells/per well were plated in 6 well dish and incubated

O/N in normal growth conditions. On day two, the growth medium was replaced with

serum free media (SFM) (no EGF) and the cells were incubated for an additional 16

hours. SFM was then replaced with SFM +/- 10 nM EGF and cells were incubated four

more hours. At this time the cells were lysed with appropriate buffer (see western blotting or polysome gradients). When performing RNA transfections the SFM was replaced with

SFM +/- 10 nM EGF at the time of the RNA transfection with cells harvested and

luciferase activity measured after four hours.

Human Phospho-Kinase Proteome Array

Lysate were prepared per manufacture instructions (R&D Systems). On the first

day, The Human Phospho-Kinase Array Proteome ProfilerTM Array was divided into two

parts (A and B) to maximize sensitivity and minimize cross-reactivity. Parts A and B

were incubated in the same lysate preparation but in separate wells of the 8-Well Multi- dish (provided). 1.0 mL of Array Buffer 1 was pipetted into each well of the 8-Well

Multi-dish to serve as a blocking buffer. Flat-tip tweezers were used to remove each membrane from between the protective sheets. Part A membrane and one Part B membrane were placed into adjacent wells of the 8-Well Multi-dish with the number on the membrane facing upward. The lid was placed on the dish that was then incubated for one hour on a rocking platform shaker. The tray was oriented so that each membrane rocked end to end in its well. While the membranes were blocking, samples were prepared by adding up to 334 μL of cell lysate to 1666 μL of Array Buffer 1 with the final volume of 2.0 mL adjusted with Lysis Buffer 6 as necessary. After incubation,

Array Buffer 1 was aspirated from the 8-Well Multi-dish and 1.0 mL of the prepared samples was added to both the Part A and Part B membrane. The covered plates were incubated overnight at 4 °C on a rocking platform shaker.

The next day, each membrane was removed and placed into individual plastic containers with 20 mL of 1X Wash Buffer. The corresponding parts (A and B) of the membrane were washed in the same container at this point with 1X in Wash Buffer for 10 minutes on a rocking platform shaker three times. For each Part A membrane, 20 μL of reconstituted Detection Antibody Cocktail A (red cap) was diluted to 1.0 mL with 1X

Array Buffer 2/3 and pipetted into a clean 8-Well Multi-dish. Each Part A membrane was removed from its wash container, allowing excess Wash Buffer to drain from the membrane, and placed in the 8-Well Multi-dish containing the diluted Detection

Antibody Cocktail A. The procedure was repeated for each Part B membrane except diluted Detection Antibody Cocktail B (blue cap) was used. Dishes were then incubated for 2 hours at room temperature on a rocking platform. Each membrane was removed and placed into individual plastic containers with 20 mL of 1X Wash Buffer. At this point, the corresponding parts (A and B) of the membrane should be washed in separate containers to minimize detection antibody cross-reactivity. Each membrane was washed with 1X Wash Buffer for 10 minutes on a rocking platform shaker three times.

The Streptavidin-HRP was diluted in 1X Array Buffer 2/3 using the dilution factor on the vial label and 1.0 mL was pipetted into each well of a clean 8-Well Multi- dish. Each membrane was removed from its wash container, allowing excess Wash

Buffer to drain from the membrane, and placed in the 8-Well Multi-dish containing the diluted Streptavidin-HRP. The covered dish was incubated for 30 minutes at room temperature on a rocking platform shaker. The wash step was then repeated three times.

Each membrane was removed from its wash container, allowing excess Wash Buffer to drain from the membrane by blotting the lower edge onto paper towels. Each membrane

was placed on the bottom sheet of the plastic sheet protector with the identification

number facing up, placing corresponding Part A and Part B membranes end-to-end.

1 mL of the prepared Chemi Reagent Mix was pippetted evenly onto each set of membranes and incubated for 1 minute. Excess detection buffer was removed and membranes were exposed to X-ray film for 1-10 minutes.

CHAPTER III

REGULATION OF THE FMR1 IRES IN NEURONAL-LIKE CELL LINES

Introduction

The mRNA and protein generated from the FMR1 gene in neurons is localized to

dendrites (Feng, Gutekunst et al. 1997; Weiler, Irwin et al. 1997). The FMR1 protein,

FMRP, is synthesized in response to neural activity and its function as an RNA binding

protein influences the translational level of other dendritically localized mRNAs (Brown,

Jin et al. 2001; Miyashiro, Beckel-Mitchener et al. 2003; Todd, Mack et al. 2003; Weiler,

Spangler et al. 2004). FMRP is also part of the RISC complex (Caudy, Myers et al. 2002;

Ishizuka, Siomi et al. 2002) a set of proteins that interact with micro-RNAs or short

interfering RNAs to inhibit translation and or degrade the RNA, respectively.

Regulating the synthesis of FMRP is important for cellular function. FMRP over-

expression leads to a defect in dendritic architecture, synaptic differentiation, and

abnormal behaviors (Peier, McIlwain et al. 2000; Pan, Zhang et al. 2004). Alternatively,

the absence of FMRP in Fragile X Syndrome (FXS) leads to alterations in synaptic

plasticity resulting in mental retardation (Bagni and Greenough 2005). FXS develops

from an expansion of the CGG nucleotide repeats in the 5’ leader of the FMR1 gene

(Pieretti, Zhang et al. 1991; Hoogeveen and Oostra 1997; Kaufmann and Reiss 1999).

Normal individuals carry from 5 – 60 repeats while those with FXS carry over 230 repeats. The expansion can lead to hypermethylation of the gene thereby inhibiting transcription. In some cases transcription of the gene occurs (Tassone, Hagerman et al.

2000; Tassone, Hagerman et al. 2001) but translation of the mRNA is inhibited by the

presence of the CGG repeat expansion (Feng, Zhang et al. 1995). The CGG repeats are

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evolutionarily conserved in mammals suggesting that the repeats have some function

aside from inhibiting transcription and translation (Eichler, Kunst et al. 1995).

The FMR1 mRNA is translated through both cap-dependent and cap-independent

mechanisms (Chiang, Carpenter et al. 2001). All mRNAs are capped, but only a subset of

mRNAs are translated in a cap-independent manner through internal ribosomal entry sites

(IRESes) located in the 5’ leader and in some cases in the open reading frame (Merrick

2004; Komar and Hatzoglou 2005). IRES-dependent translation is thought to be utilized

when cap-dependent translation is inhibited. This occurs during normal physiological

processes including mitosis, but also in response to stressful events such as apoptosis

(Cornelis, Bruynooghe et al. 2000; Holcik, Sonenberg et al. 2000; Lewis and Holcik

2005). In the nervous system, numerous dendritically localized mRNAs contain IRESes

including those encoding for the alpha subunit of CAMKII, activity-related cytoskeletal

protein, and the neurotrophin receptor TrkB (Pinkstaff, Chappell et al. 2001; Dobson,

Minic et al. 2005). The high preponderance of dendritically localized mRNAs containing

IRESes suggests that IRES-dependent translation is an important protein synthesis

mechanism in dendrites.

The goals of this study were to confirm a previous study that the FMR1 5' leader

mediates internal initiation of translation (Chiang, Carpenter et al. 2001), identify regions

in the FMR1 5' leader critical for IRES activity, and to determine if FMR1 IRES activity

is affected by cellular processes in which FMRP participates. Initially, the FMR1 5'

leader was re-examined for IRES activity using dicistronic DNA constructs. It was

determined that the leader contained a cryptic promoter, compelling the use of RNA

constructs. Translation assays using RNA both in vitro and ex vivo demonstrated that the

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FMR1 5' leader does contain an IRES and that IRES-dependent translation may be an

important mechanism for the synthesis of FMRP in vivo. A dissection of the 5' leader

showed that the 5' 45 nucleotides (nt) as well as the CGG repeats are important for

internal initiation. Finally, multiple cellular stimuli including exposure to KCl and

intracellular acidification as models for neural activity and exposure to

polyinosinic:polycytidylic acid as a model for the presence of double stranded RNA

resulted in alterations of FMR1 IRES activity.

I began this work as a Professional Research Assistant in the Krushel Lab along

with two other lab members, Erica Kube and Stephanie Timmerman, before attending the

graduate program at The University of Colorado – School of Medicine. The combination

of our work is represented in Figures 3.1, 3.2, and 3.4. The remaining Figures in this

chapter – 3.3, 3.5, and 3.6 – are the results of my individual studies performed after re-

joining the Krushel Lab as a graduate student in the Department of Biochemistry and

Molecular Genetics.

Results

The FMR1 5' leader directs expression of the second cistron in a dicistronic DNA construct

Viral IRESes are denoted by being relatively long (> 200nt), guanosine/cytosine

(G/C) nt rich, and containing upstream open reading frames (uORFs). The FMR1 5' leader exhibits a subset of these characteristics being approximately 240 nt (depending upon the number of CGG repeats) and is > 80% G/C rich, but it does not contain any uORFs. To confirm a previous report that the FMR1 5' leader contained an IRES

(Chiang, Carpenter et al. 2001), the leader was inserted into the intercistronic region of a

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dicistronic luciferase construct. Two negative controls were used, the multiple cloning site (MCS) in the intercistronic region (pRF aka RP) and the β-globin 5' leader. The β- globin 5' leader was chosen since the β-globin mRNA is translated exclusively in a cap- dependent manner (Lockard and Lane 1978). The encephalomyocarditis (EMCV) virus

IRES was chosen as the positive control (Jang, Krausslich et al. 1988). The constructs were transfected into the C6 glioma and N2a neuroblastoma cell lines. After 24 hrs the cells were harvested and assayed for Renilla and Photinus luciferase. The

Photinus:Renilla luciferase (P:R) ratio obtained from the control dicistronic construct

(pRF aka RP) was normalized to one. A ratio above one would indicate IRES activity.

Both the EMCV IRES and the FMR1 5' leader exhibited P:R ratios significantly higher than that observed from the pRF (and β-globin) construct. Indeed, the P:R ratio obtained from the FMR1 5' leader was approximately 30 and 60 fold higher in C6 and N2a cells respectively (Figure 3.1A). The level of FMR1 IRES activity was higher than that observed from the EMCV IRES. This initial result suggests that the FMR1 5' leader may contain an IRES.

The FMR1 5' leader contains a cryptic promoter

In addition to internal initiation, increased levels of Photinus luciferase protein can be generated from the dicistronic luciferase constructs through cryptic splicing or cryptic promoter activity. For example, the presence of a cryptic promoter in the 5' leader will lead to the production of a monocistronic Photinus luciferase mRNA (Han and

Zhang 2002; Van Eden, Byrd et al. 2004) and artificially increase the P:R ratio. To determine if cryptic promoter activity was present in the FMR1 5' leader, the dicistronic

luciferase constructs with or without the SV40 promoter and intron were transfected into

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Figure 3.1 The FMR1 5’ leader exhibits putative IRES-activity, but also contains a cryptic promoter (A) To identify IRES activity, dicistronic luciferase DNA constructs containing the multiple cloning site (MCS) from pRF (RP)-negative control, the 5’ leader from β-globin-negative control or FMR1, or the EMCV IRES-positive control inserted into the intercistronic region were transfected individually into C6 cells or N2a cells. Luciferase activity is shown as the ratio of Photinus luciferase to Renilla luciferase (P:R) and is normalized to the activity obtained from the control construct, pRF (RP). A P:R ratio that is above that obtained from pRF(RP) indicates the presence of an IRES. (B) To control for cryptic promoter activity, dicistronic luciferase DNA constructs containing the β-globin or FMR1 5’ leader or the EMCV IRES with or without the SV40 promoter were transfected into C6 cells. The Photinus luciferase activity from each transfection is shown. Each experiment was performed in triplicate, n = 3.

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C6 cells. Photinus luciferase activity from the promoterless constructs containing the pRF MCS, β-globin 5' leader, and EMCV IRES was very low, less than 1% of the

Photinus luciferase activity obtained from the constructs with the intact promoter (Figure

3.1B). This result confirms previous studies indicating that these leaders do not contain a cryptic promoter (Dobson, Minic et al. 2005; Wang, Weaver et al. 2005). However, the promoterless construct containing the FMR1 5' leader generated approximately 15% of the 'total' Photinus luciferase activity (Figure 3.1B). After subtracting the minor contribution of the cryptic promoter to the translation of the second cistron, the data still suggests that the FMR1 5' leader has an IRES, but it does temper this conclusion.

The FMR1 5' leader exhibits IRES activity from a dicistronic RNA

To determine more unambiguously whether the FMR1 5' leader contains an IRES, the dicistronic constructs were transcribed in vitro eliminating the possibility of alternative splicing and alternate promoters. Transfecting the mRNA into C6 cells did provide evidence of IRES activity (Figure 3.2A). The P:R ratio obtained from the dicistronic luciferase mRNA containing the FMR1 5' leader was approximately 4.5 fold higher than the β-globin control. Although the P:R ratio generated from the FMR1 5' leader was substantially lower when comparing the RNA to DNA transfections, the results still indicate that the FMR1 5' leader contains an IRES.

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Figure 3.2 A

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Figure 3.2 Ex vivo and in vitro studies demonstrating IRES activity mediated by the FMR1 5’ leader (A) To control for cryptic promoter activity, capped dicistronic luciferase RNA containing the 5’ leader from the β-globin or FMR1 mRNA inserted into the intercistronic region was transfected individually into C6 cells. Luciferase activity is shown as the ratio of Photinus luciferase to Renilla luciferase (P:R) and is normalized to the activity of the β-globin construct. The experiment was performed in triplicate, n = 3. (B) Monocistronic Photinus luciferase mRNA containing the β-globinor FMR1 5’ leader was translated in rabbit reticulocyte lysate in the presence of increasing concentrations of cap analog to compete with the cap structure for eIF4E to determine of the transcripts could maintain initial levels of translation. The initial level of Photinus luciferase activity from each monocistronic mRNA was normalized to 100. (C) To determine if the FMR1 5’ leader could maintain translation levels when cap-dependent translation is inhibited in cells, monocistronic Photinus luciferase constructs containing the β-globin, EMCV, or FMR1 5’ leader were co-transfected with either a plasmid expressing hypophosphorylated 4E-BP1 or a control plasmid and assayed for luciferase activity. The activities obtained in cells co-transfected with hypophosphorylated 4E-BP1 is represented as a percentage of the activity obtained in cells co-transfected with the control plasmid. The experiment was performed in triplicate, n = 3.

107

Translation of a monocistronic mRNA in vitro and ex vivo indicates a key role for

IRES-dependent translation mediated by the FMR1 5' leader

The dicistronic luciferase assay is useful to identify sequences that can internally initiate translation, but it does not indicate the role of an IRES in a monocistronic mRNA, the context in which the IRES is normally found in cellular mRNA. Consequently, two approaches were utilized to determine whether the FMR1 IRES is a major contributor to the translation of a monocistronic capped mRNA. Initially, in vitro transcribed monocistronic mRNA containing the Photinus luciferase open reading frame (ORF) and the β-globin or FMR1 5' leader was translated in rabbit reticulocyte lysate. The overall level of Photinus luciferase synthesis was reduced by approximately 40% when the

FMR1 5' leader was present. This result is not surprising since cap-dependent translation of a short unstructured 5' leader (β-globin) is very efficient. Increasing concentrations of cap analog were added to the lysate to compete with the cap structure for eIF4E and inhibit cap-dependent translation. Translation of the mRNA containing the β-globin 5' leader decreased as the concentration of cap analog increased (Figure 3.2B). This result demonstrates that the β-globin mRNA is being translated in a cap-dependent manner. On the other hand, translation of the mRNA containing the FMR1 5' leader was only moderately affected (Figure 3.2B); translation of the Photinus luciferase cistron decreased by only 15% at the highest concentration of cap analog. This result not only indicates that the mRNA containing the FMR1 5' leader is being translated in a cap- independent manner, but that it may be the major mechanism for its translation.

To determine the role of the FMR1 IRES within a cell, cap-dependent translation was inhibited ex-vivo. The 4E-Binding Protein 1 (4E-BP1) binds and sequesters eIF4E

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preventing cap-dependent translation (Richter and Sonenberg 2005), but phosphorylation

of 4E-BP1 decreases its affinity to eIF4E. Consequently, C6 cells were transfected with a

construct coding for a mutant of 4E-BP1 (4E-BPmut) with the two key phosphorylation

sites mutated (T–37–A/T –46 –A) or a control plasmid (Gingras, Gygi et al. 1999).

Monocistronic constructs containing the β-globin, EMCV, or FMR1 5' leader were co-

transfected. In the presence of over-expressed 4E-BPmut, the level of Photinus luciferase

activity derived from the mRNA containing the β-globin 5' leader decreased by 72%

(Figure 3.2). However, translation from the mRNAs containing the FMR1 or EMCV 5'

leader only decreased by 19% and 27%, respectively (Figure 3.2C). Since 81% of the

luciferase activity remains when cap-dependent translation is inhibited, it indicates that

IRES-dependent translation may be the primary mechanism for translation of the FMR1 mRNA in vivo.

Endogenous FMRP expression is unaffected by reducing cap-dependent translation

To examine whether IRES-dependent translation is utilized for the synthesis of

endogenous FMRP, cap-dependent translation was inhibited by treating C6 cells with

rapamycin. The kinase mammalian target of rapamycin (mTOR) is a key link in the

promotion of cap-dependent translation by phosphorylating 4E-BP and p70 S6 kinase. An

exposure of 24 hrs to 20 µM rapamycin actually led to a modest increase in FMRP

expression (Figure 3.3). On the other hand, phosphorylation of p70 S6 kinase was

abolished demonstrating that the mTOR pathway was inhibited and the expression level

of eIF4E was decreased indicating cap-dependent translation was repressed (Figure 3.3).

Taken together with the 4E-BP experiment, these results indicate that IRES-dependent

translation is a major mechanism for the synthesis of FMRP.

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Figure 3.3 A rapamycin FMRP

eIF4E

p-p70S6K

Gapdh

B eIF4E

Jun B

FMRP

Gapdh C

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Figure 3.3 FMRP expression is maintained when cap-dependent translation is reduced by rapamycin or eIF4E siRNA Additional assays to measure translation initiation of the FMR1 5’ leader when cap-dependent translation is downregulated were performed (A) Lysates from untreated or rapamycin treated C6 cells were analyzed for FMRP, phosphorylated p70 S6 kinase, and eIF4E. Shown is a representative Western blot for each experiment, n = 3. (B) siRNA directed against eIF4E or a nonsense siRNA were transfected into C6 cells for 72 hr. Lysates from these cells were analyzed for eIF4E, FMRP, JunB and Gapdh. Gapdh was used as a loading control since it has an extended half-life. Shown is a representative Western blot for each experiment, n = 3. (C) Western blots of lysates from cells treated with eIF4E or a nonsense siRNA. Expression level of the proteins were quantitated using ImageQuant software (n = 3) and were normalized to Gapdh levels.

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Multiple regions in the 5’ leader contribute to FMR1 IRES activity

A deletion analysis was performed to identify the region(s) in the FMR1 5’ leader

that are important for IRES activity. Serial 5’ truncations ranging from 11 to 53 nt were

inserted into the dicistronic luciferase construct and the mRNA was transfected into C6

cells. Deletion of the 5’ 45 nt (-253 - -209) resulted in the largest decrease in IRES

activity (Figure 3.4A). The P:R ratio derived from the 3’ 208 nt was only 1.5 fold over

that obtained from the β-globin control. Truncation of an additional 42 nt (-208 - -167)

abolished all IRES activity. Additional truncations of 46 nt (-166 - -121) actually led to an

increase in the P:R ratio of approximately 1.5 fold over the control value. Further

truncations of 53 and 13 nt (-120 - -54) that encompassed the CGG repeats resulted in a

decrease and complete loss of IRES activity, respectively. These results indicate that 1)

the 5’ end of the 5’ leader is important for wild-type IRES activity, 2) an internal region may be inhibitory, and 3) the nt -120 - -54 exhibit a basal level of IRES activity.

Interestingly, this latter region encompasses the CGG repeats of which nine are contained

in the present 5’ leader.

Changes in intracellular pH regulate the FMR1 IRES

To determine the regulatory elements in the FMR1 IRES, C6 cells were exposed

to 500 µM amiloride for 24 hrs to block the Na+/H+ antiporter. Intracellular acidification

inhibits neural activity and is a model of an inactive neuron (Kaila 1998). The P:R ratio from the dicistronic mRNA containing the full-length 5’ leader dramatically decreased in the presence of amiloride (Figure 3.4A). However, only subtle differences in the P:R

ratio were observed from truncations of the 3’ 208 nt. The minimal level of IRES activity

remained in the shorter leaders. This result implies that a decrease in intracellular pH

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Figure 3.4 Truncations and ameloride treatment identify regions in the FMR1 5’ leader important for IRES activity (A) Dicistronic luciferase mRNA containing the β- globin, FMR1, or serial 5’ truncations of the FMR1 5’ leader inserted into the intercistronic region were transfected into C6 cells. C6 cells were exposed to ameloride for 24 hr or untreated. Luciferase activity is shown as the P:R ratio and is normalized to the activity from the β-globin mRNA. (B) Dicistronic luciferase mRNA containing the full length FMR1 5’ leader, FMR1 5’ leader with an internal deletion of the CGG repeats (FMRΔCGG), or the β-globin 5’ leader inserted into the intercistronic region was transfected into C6 cells. Luciferase activity is shown as the P:R ratio and is normalized.

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inhibits FMR1 IRES activity and this effect is mediated by repressing the IRES-

promoting region located at the 5’ end of the 5’ leader.

The CGG repeats contribute to FMR1 IRES activity

The basal level of IRES activity exhibited in the 5’ leader containing the 3’ 120 nt

was not affected by changes in intracellular pH. An additional truncation deleting the

CGG repeats abolished all IRES activity. To further characterize the role of the CGG

repeats in the FMR1 IRES, the repeats were internally deleted within the full-length 5’

leader. Transfection of the dicistronic mRNA containing the FMR1 5’ leader with the

CGG repeats deleted exhibited an approximately 50% decrease in the P:R ratio compared

to the full-length 5’ leader (Figure 3.4B). This result demonstrates the importance of the

CGG repeats for internal initiation mediated by the FMR1 5’ leader.

FMR1 IRES activity is affected by multiple cellular stimuli

IRES-dependent translation is affected by multiple cellular stimuli (Nevins,

Harder et al. 2003). We sought to determine whether the FMR1 IRES is regulated by

environmental stimuli which regulate the processes in which FMRP participates.

Neuronal activity leads to translation of FMR1 mRNA (Weiler, Irwin et al. 1997; Gabel,

Won et al. 2004) and we modeled this phenomenon by treating cells with 50 mM KCl for

30 or 150 min. The short KCl exposure led to a 32% increase in the P:R ratio from the dicistronic mRNA containing the FMR1 5’ leader (Figure 3.5A). However, the longer

KCl treatment resulted in a 28% decrease in the P:R ratio. Moreover, the FMR1 P:R ratio

after the 150 min. treatment was only one-third higher than that obtained from the control dicistronic mRNA (Figure 3.5A). This result indicates that cellular depolarization differentially affects FMR1 IRES activity depending upon its duration.

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Figure 3.5 A

KCL treatment (min) B FMRP

Gapdh

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Figure 3.5 Exposure to KCl alters FMR1 IRES activity and FMRP expression (A) Dicistronic luciferase mRNA containing the β-globin or FMR1 5’ leader inserted into the intercistronic region was transfected into C6 cells and exposed to 50 mM KCl for 30 or 150 min. After seven hr the cells were assayed for Photinus and Renilla luciferase activity. (B) Lysates from cells treated in (A) were analyzed for FMRP and Gapdh (as a loading control) using Western blots. Shown is a representative Western blot; each experiment was performed in triplicate, n = 3. (C) Protein expression was quantitated using ImageQuant software; FMRP levels were normalized to Gapdh expression. .

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To examine whether KCl also affects FMRP expression, Western blots were

performed from lysates obtained from the treated and untreated cells. Changes in

endogenous FMRP levels mirrored that observed from FMRP IRES (Figure 3.5B, C). An

increase of 58% was seen after a 30 min KCl treatment, whereas a 150 min treatment led

to a 40% decrease in FMRP expression.

FMRP has been localized to the RNA-induced silencing complex (RISC), a nuclease complex that mediates RNA interference (RNAi). Deletion of FMRP leads to a loss of RNAi (Siomi, Ishizuka et al. 2004). To determine if the presence of double stranded RNA affects FMR1 IRES activity, C6 cells were exposed to 500 µg/ml of polyinosinic:polycytidylic acid (poly I:C), a double stranded polyribonucleotide. After a

7 hr exposure to poly I:C., the FMR1 P:R ratio increased by 41% (Figure 3.6A). This result indicates a possible positive feedback mechanism to stimulate FMRP synthesis in response to double stranded RNA and it predicts that RNAi activity will increase FMR1 translation in an IRES-dependent manner. Tempering this conclusion was that expression of endogenous FMRP did not change after a 7 hr exposure to poly I:C (Figure 3.6B, C).

As was observed from the KCl experiments, it is possible that FMRP expression may be upregulated at different timepoints following poly I:C exposure.

Discussion

Summary of findings

In summary, this study demonstrated that the FMR1 5' leader contains an IRES whose activity is dependent upon the 5' 45 nt as well as the CGG repeats in the 5' leader.

Moreover, internal initiation appears to be an important mechanism for the translation of the FMR1 mRNA. This conclusion is supported by the observation that synthesis of

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Figure 3.6 A

B FMRP

Gapdh

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Figure 3.6 Exposure to poly I:C alters FMR1 IRES activity (A) Dicistronic luciferase mRNA containing the β-globin or FMR1 5’ leader inserted into the intercistronic region were transfected into C6 cells and exposed to 500 µg/ml of poly I:C. After seven hr the cells were assayed for Photinus and Renilla luciferase activity. (B) Lysates from cells treated in (A) were analyzed for FMRP and Gapdh (as a loading control) using Western blots. Shown is a representative Western blot; each experiment was performed in triplicate, n = 3. (C) Protein expression was quantitated using ImageQuant software; FMRP levels were normalized to Gapdh expression.

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FMRP is maintained when cap-dependent translation is inhibited by knocking-down

eIF4E expression or rapamycin treatment. Inhibiting cap-dependent translation of

reporter mRNAs containing the FMR1 5’ leader, both in vitro and ex vivo, resulted in

only a small diminution in protein synthesis, while translation of the endogenous FMR1

mRNA was enhanced. Regulation of internal initiation of translation mediated by the

FMR1 5’ leader mirrors that of FMR1 synthesis in vivo. Taken together, this study

indicates that IRES-dependent translation of the FMR1 may be a major contributor to the

synthesis of FMRP in vivo.

Cryptic promoters require the use of RNA reporter constructs

Our results show that the FMR1 5' leader contains a cryptic promoter, an

observation that has been noted in other 5' leaders (Han and Zhang 2002; Liu, Dong et al.

2005). The presence of elements influencing transcription is not surprising as transcriptional elements are located throughout a gene. While the FMR1 5' leader affects transcription when present as DNA, the same region promotes internal initiation as RNA as deduced from both in vitro and ex vivo experiments using monocistronic and dicistronic mRNA. RNA for these assays was produced from in vitro transcription and this process could yield a FMR1 5' leader with a secondary structure different than what occurs in the cell. Indeed, it is likely that proteins including IRES transactivating factors

(ITAFs, see below) bind to the FMR1 5' leader and alter its structure in vivo. However, viral IRESes whose activity depends extensively upon secondary structure yield robust

IRES activity from in vitro transcribed RNA (Tsukiyama-Kohara, Iizuka et al. 1992;

Bochkov and Palmenberg 2006) and are suitable for structural analysis (Pfingsten,

Costantino et al. 2006).

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The evolutionarily conserved CGG repeats can upregulate translation of the FMR1

mRNA

The CGG repeats, which are amplified in FXS, are evolutionarily conserved in

mammals (Eichler, Kunst et al. 1995). I suggest that the CGG repeats are retained due to

their ability to promote translation and specifically internal initiation of translation. This

hypothesis is supported by evidence indicating that mRNA containing the normal number

of CGG repeats translates at a higher level compared to mRNA absent of the repeats or contains a higher number of repeats (Chen, Tassone et al. 2003). Moreover, we found that

deleting the CGG repeats significantly decreased FMR1 IRES activity. The mechanism

by which the repeats affect IRES activity is open to speculation. Secondary structure is

important for viral IRESes and their ability to recruit canonical factors and the ribosome

(Pestova, Kolupaeva et al. 2001). Minor changes in the RNA structure can dramatically

alter viral IRES activity (Guest, Pilipenko et al. 2004; De Jesus, Franco et al. 2005).

Since the 3’ 120 nt are able to mediate internal initiation, the ribosome must bind

somewhere in this region and the CGG repeats may create a structure conducive for

ribosomal recruitment. On the other hand, it has been proposed that expansion of the

CGG repeats (~50 – 200) in the Fragile X pre-mutation allele sequesters an RNA binding

protein and indirectly affects the function of other mRNAs (Hagerman and Hagerman

2004). Thus, the CGG repeats may bind an IRES trans-activating factor that directly

recruits the translational machinery or may act as a molecular chaperone and alter the

secondary structure, which in turn recruits the translational machinery.

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Characterization of the FMR1 5’ leader

Deletion of the 5' 45 nt (or more specifically the nt 18 – 45 from the 5' end) of the

FMR1 5' leader yielded the largest decrease in IRES activity. This segment is also highly conserved in mammals. In general, viral IRESes are greater than 200 nt in length and it would be of interest if a substantially smaller RNA segment of the FMR1 5' leader could internally initiate translation. This observation is not unprecedented as we have found that a region of 50 nt in the 5' leader of the amyloid precursor protein yields IRES activity

(Beaudoin, Poirel et al. 2008). However, the 5' deletion analysis as discussed above indicates that the ribosome binds further downstream. It is likely that the 5' 45 nt do not contain an IRES, but are a crucial cis-element that enhances IRES activity by affecting downstream RNA secondary structure, perhaps through protein binding. Of interest is a region of ten contiguous nt (nt 33 – 42 from the 5' end) of which nine are pyrimidines making this a potential binding site for the polypyrimidine binding protein PTB) and its neural homolog nPTB. PTB aside from its role in RNA splicing is an important ITAF for many eukaryotic IRESes (Sawicka, Bushell et al. 2008).

IRES activity contributes to the regulation of FMRP synthesis during multiple neuronal events

FMRP is synthesized in response to neural activity (Weiler, Irwin et al. 1997;

Gabel, Won et al. 2004) and in particular, a brief exposure to KCl stimulates FMR1 synthesis in neuronal dendrites (Greenough, Klintsova et al. 2001). In this study, IRES activity mediated by the FMR1 5’ leader was also regulated by the duration of KCl exposure; a short exposure increased and a longer exposure decreased FMR1 IRES activity. Moreover, intracellular acidification associated with decreased neural activity

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also inhibited FMR1 IRES activity. These results suggest that neural activity of differing

intensity or duration may produce distinct changes in IRES-dependent translation

mediated by the FMR1 5’ leader and that IRES-dependent translation is a mechanism contributing to the synthesis of FMRP in neurons. These results also indicate that a feedback mechanism exists that is dependent upon the duration of the calcium influx through voltage gated calcium channels stimulated by KCl. Indeed, extent and duration of intracellular calcium can regulate the translation of other mRNAs (Finkbeiner and

Greenberg 1998; Mengesdorf, Althausen et al. 2001).

FMRP is associated with the RISC complex (Caudy, Myers et al. 2002; Ishizuka,

Siomi et al. 2002) and my results indicate that the presence of double stranded RNA stimulates IRES-dependent synthesis of FMRP. This result implicates a positive feedback

mechanism regulating the synthesis of FMRP and the level of FMRP could regulate the

activity or the targets of the RISC complex. Moreover, the results indicate that many

cellular processes to which FMRP contributes affect FMRP IRES activity and

consequently FMRP synthesis. This observation would explain the dendritic localization

of FMR1 mRNA since FMRP expression could be regulated post-transcriptionally.

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CHAPTER IV

IRES-DEPENDENT TRANSLATION IS THE PRIMARY MECHANISM

CONTRIBUTING TO AURORA A OVER-EXPRESSION IN A SUBSET OF

EPITHELIAL CELL LINES

Introduction

Aurora A is a serine/threonine kinase that plays a crucial regulatory role during mitotic events including centrosome duplication, separation and maturation as well as mitotic spindle stabilization (Adams, Carmena et al. 2001; Nigg 2001; Fu, Bian et al.

2007). Regulation of Aurora A expression is tightly controlled with both the mRNA and protein detected in late S early G2 phase, peaking in G2/M, and rapidly degrading prior to G1 phase (Honda, Mihara et al. 2000; Tanaka, Ueda et al. 2002). Aberrant expression of this kinase is detrimental to the cell. Over-expression contributes to centrosome amplification and a failure in cytokinesis creating aneuploidy, setting the stage for carcinogenesis (Zhou, Kuang et al. 1998; Littlepage, Wu et al. 2002). Numerous tumor cell lines and human tumors exhibit elevated levels of the Aurora A kinase, suggesting it may play a role in tumorigenesis (Bischoff, Anderson et al. 1998; Sakakura, Hagiwara et al. 2001; Gritsko, Coppola et al. 2003; Jeng, Peng et al. 2004). Alternatively, loss of

Aurora A leads to centrosomal separation defects resulting in a monopolar spindle, which in turn activates the G2/M checkpoint and eventually apoptosis (Glover, Leibowitz et al.

1995). For this reason the Aurora A kinase is considered a target for the development of anticancer drugs.

Enhanced expression of Aurora A protein in tumors is reportedly due to a concomitant increase in Aurora A mRNA owing to gene amplification and/or increased

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transcription (Tanner, Tirkkonen et al. 1994; Tanner, Tirkkonen et al. 1995; Bischoff,

Anderson et al. 1998; Zhou, Kuang et al. 1998; Tanner, Grenman et al. 2000). However,

there are examples in many cancers whereby increased Aurora A protein expression is

not accompanied by changes in mRNA levels (Lai, Tseng et al. 2010; Gritsko, Coppola et

al. 2003; Jeng, Peng et al. 2004). These results suggest that post-transcriptional processes including enhanced protein synthesis and/or protein stability are also likely contributing to the increased Aurora A kinase levels.

The major regulatory step in protein synthesis occurs at the initiation of translation (Palmiter 1972). Most eukaryotic mRNAs are thought to initiate translation in a cap-dependent manner. This mechanism involves the binding of the preinitiation complex to the methyl-7-guansine (m7G) cap structure at the 5’ end of the mRNA and scanning of the 40S ribosome to the first initiator codon in a proper context (Kozak 1987)

(reviewed in (Gingras, Raught et al. 1999; Merrick 2004)). In a subset of cellular mRNAs, an alternative mechanism to initiate translation occurs in which the preinitiation complex internally binds the 5’ leader or untranslated region (UTR) (Jackson, Hunt et al.

1995; Jackson and Kaminski 1995). The binding site is referred to as an internal

ribosome entry site (IRES). During periods in which cap-dependent translation is

decreased, including in response to cell stress or mitosis, IRES-dependent translation is

proposed to be maintained or elevated (Stein, Itin et al. 1998; Holcik, Lefebvre et al.

1999; Pyronnet, Pradayrol et al. 2000; Stoneley and Willis 2004). Indeed, many mRNAs

translated during mitosis contain IRESes. For example, IRES-dependent translation of the ornithine decarboxylase (Pyronnet, Pradayrol et al. 2000) and PITSRLE p58

(Cornelis, Bruynooghe et al. 2000) mRNA occurs exclusively during mitosis (Holcik,

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Lefebvre et al. 1999). Additionally, most of the small subset of eukaryotic IRESes identified to date are located in mRNAs that encode proteins that affect tumorigenesis.

These proteins include oncogenes (c-myc) (Stoneley, Paulin et al. 1998), growth factors

(FGF2) (van der Velden and Thomas 1999; Creancier, Morello et al. 2000; Martineau, Le

Bec et al. 2004), growth factor receptors (TrkB) (Dobson, Minic et al. 2005), pro- and anti-apoptotic factors (XIAP and APAF-1, respectively) (Holcik and Korneluk 2000;

Mitchell, Spriggs et al. 2003), and angiogenic factors (VEGF) (van der Velden and

Thomas 1999). Deregulating IRES-dependent translation of these mRNAs could be a mechanism to promote cell survival and uncontrolled cellular proliferation during carcinogenesis.

In this study, I chose multiple cell lines that differentially express Aurora A to identify mechanism(s) contributing to its over-expression. Transcription, mRNA stability, cap-dependent translation and protein stability could not account for the increased Aurora

A protein expression in a subset of cell lines. However, I identified an IRES in the 5’ leader of the Aurora A mRNA. Aurora A IRES activity positively correlated with Aurora

A protein levels. I propose there is a switch from cap-dependent to IRES-dependent translation of the Aurora A mRNA that contributes to over-expression of the protein. In turn, this enhanced IRES activity may be a key determinant in generating genomic instability that may eventually result in cellular immortalization.

Results

Enhanced protein synthesis contributes to over-expression of the Aurora A kinase

Increased Aurora A kinase expression is proposed to contribute to cellular immortalization (Kollareddy, Dzubak et al. 2008). To identify mechanisms contributing

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to this enhancement, Aurora A protein expression was examined in a variety of cells,

focusing on breast epithelial cell lines. Aurora A protein levels were quantified in two

finite lines, normal lung fibroblasts (WI-38) and human mammary epithelial cells

(HMEC). Aurora A protein expression in these cells was chosen to represent basal protein levels and compared to the following immortalized cell lines: non-tumorigenic breast epithelial cell lines (MCF10A and MCF12A), and tumorigenic epithelial cell lines

(MCF-7 and HeLa S3) from breast and cervix, respectively. Lysates were analyzed via

Western blotting for Aurora A and Gapdh (as a loading control). Expression of Aurora A kinase in the control cell lines, WI-38 and HMEC, were similar and comparable to that observed in MCF-7 cells (Figure 4.1A). However, Aurora A kinase expression was 2 to

4.2 fold higher in MCF10A, MCF12A and HeLa S3 cells (Figure 4.1A). Three out of the

4 immortalized cell lines demonstrated Aurora A protein levels similar to those observed in many breast and cervical cancer (Kollareddy, Dzubak et al. 2008).

The Aurora A gene is transcribed and the mRNA is translated during late S phase

and peaks during G2/M phase of the cell cycle (Honda, Mihara et al. 2000; Tanaka, Ueda

et al. 2002). Therefore, it is possible that differences in the number of cells in these

phases from an asynchronous population could contribute to the observed differences in

Aurora A protein levels. However, flow cytometry analysis (FACS) of these

asynchronous populations did not show a correlation with the percentage of cells in

G2/M and Aurora A protein levels (Figure 4.2). Therefore alterations in transcription,

translation and/or protein stability are likely contributing to increased Aurora A kinase

expression in MCF10A, MCF12A and HeLa S3 cells.

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Figure 4.1 A Aurora A Gapdh

C **

* p<.05

**p<.005

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Figure 4.1 Post-transcriptional regulation contributes to enhanced expression of the Aurora A protein in subset of immortalized cell lines (A) Aurora A protein expression was analyzed via western blotting. Aurora A protein levels were determined using ImageQuant and Gapdh was used as a loading control. The Aurora A to Gapdh ratio in WI-38 cells were set to one and used to normalize Aurora A expression in the other lines. n=6 + standard deviations (SD) (B) Total RNA was isolated and analyzed via qRT-PCR with Gapdh as a reference target (see Chapter II for details). Results were normalized to the Aurora A mRNA level in WI-38 cells. n=3 + SD (C) Results from (A) and (B) were used to determine Aurora A protein expression relative to Aurora A mRNA levels. The ratio of the normalized Aurora A protein levels to normalized Aurora A mRNA levels are shown.

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Figure 4.2 G2/M populations of asynchronous cells do not correlate with Aurora A protein levels To determine if increased Aurora A protein levels were due to an increased population of cells in the G2/M of the phase of the cell cycle. No correlation was observed. Expression of both Aurora A protein and mRNA levels peak in G2/M but Aurora A mRNA levels were similar between high and low protein expressing lines. Taken together these results indicate increased Aurora A protein levels are the result of post-transcriptional regulation. The percent of cells in G1, S, or G2/M from asynchronous populations of each cell line is shown as determined by FACs. n=3 + SD

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To quantify Aurora A mRNA levels, cDNA libraries were constructed from total

RNA isolated from the individual cell lines. Aurora A transcript levels from each cell line were measured by qRT-PCR and showed that mRNA levels were similar between each cell line except for a slight increase in MCF-7 cells (Figure 4.1B). Thus, generating a ratio of Aurora A protein to mRNA within each cell line showed an approximately 2-5 fold higher amount of Aurora A protein to mRNA in MCF10A, MCF12A and HeLa S3 cells compared to WI-38 and HMEC cells, and even higher when compared MCF-7 cells

(Figure 4.1C). These results indicate that increased Aurora A protein expression in the

MCF10A, MCF12A and HeLa S3 cell lines is not due to enhanced transcription of the

Aurora A gene or Aurora A mRNA stability but the result of increased protein synthesis and/or protein stability.

To identify if alterations in protein stability contributed to the differential Aurora

A expression, the half-life of the Aurora A protein was determined. Cells were harvested at 2-12 hours (hrs) after being treated with cycloheximide. The Aurora A protein levels were then analyzed via western blotting with Gapdh as a loading control since it has a half-life of 90 to 120 hrs (Sukhanov, Higashi et al. 2006). The half-life of the Aurora A protein was similar between the cell lines, ranging between 2.2 to 2.9 hrs (Figure 4.3).

This range is consistent with a previous study that found the Aurora A protein half-life to be approximately 2.5 hrs (Honda, Mihara et al. 2000). In addition, this result indicates that differences in protein stability do not contribute to the differential expression of

Aurora A protein.

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Figure 4.3 Aurora A protein stability is similar in the set of cell lines To determine if increased protein stability contributed to over-expression Aurora A in a subset of cell lines protein degradation was observed. Representative western blots used to measure the rate of Aurora A protein degradation in each cell line are shown. Top panel shows Aurora A protein levels and the bottom panel shows Gapdh protein levels used as a loading control to normalize Aurora A expression. Aurora A ½ life was determined by non-linear regression one-phase decay. Quantitation from western blotting of Aurora A protein expression levels in cells treated for 0 to 12.5 hours with cycloheximide to inhibit translation elongation. Expression level of Aurora A protein in the untreated cells (0 hr) was normalized to 100. n=3 + SD

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By order of elimination, the previous results implicated protein synthesis as one of the remaining mechanisms that could be contributing to the variable Aurora A protein levels. To confirm this hypothesis, a polysome gradient analysis was performed. Aurora

A mRNA levels were quantified in nonpolysomal, low molecular weight (LMW) polysome and high molecular weight (HMW) polysome fractions between the low

Aurora A protein expressing MCF-7 cells and high Aurora A protein expressing

MCF12A cells. Association with HMW fractions suggests increased translation initiation and/or reinitiation as the result of more efficient loading of the ribosomes onto the mRNA

(Thomas and Johannes 2007). Aurora A mRNA was most concentrated in the HMW fractions from MCF12A cells. In contrast, the majority of Aurora A mRNA levels from

MCF-7 cells resided with the LMW fractions (Figure 4.4). These results indicate translational up-regulation as a contributing mechanism to enhanced protein expression in

MCF12A cells compared to MCF-7 cells.

Cap-dependent translation initiation is increased in the immortalized cell lines

The major mechanism by which translation is regulated is at the step of initiation.

Misregulation of cap-dependent translation can lead to elevated levels of protein synthesis and tumorigenesis. For example, increased expression of the rate-limiting canonical factor eIF4E is found in many tumors (Hiremath, Webb et al. 1985; Duncan,

Milburn et al. 1987; De Benedetti, Joshi-Barve et al. 1991). Furthermore, ectopically induced over-expression of eIF4E has transforming capabilities leading to malignant phenotypes (Lazaris-Karatzas, Smith et al. 1992; Avdulov, Li et al. 2004; De Benedetti and Graff 2004). To determine if elevated eIF4E levels were contributing to the over-

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Figure 4.4 Aurora A transcripts are associated more with the HMW polysome in MCF12A cells compared to MCF-7 cells High expressing MCF12A cells and low expressing MCF-7 cells were treated with cycloheximide, collected and prepared for fractionation via a sucrose gradient (see Chapter II for details). Total RNA from the nonpolysomal fractions (containing 40S, 60S, and 80S peaks, fractions 1-2), low molecular weight polysome fractions (disome and trisome, fractions 3-4)), and high molecular weight polysome fractions (> trisome, fraction 5-6) was isolated. Quantitation of Aurora A mRNA levels associated with the different gradient fractions was measured using qRT-PCR after isolation of total RNA from each fraction. The top to bottom of the sucrose gradient is indicated. n=3 +SD

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expression of Aurora A, Western blots of lysates were analyzed. eIF4E levels were

similar in all six cell lines (Figure 4.5A). This observation suggests that a global increase

in cap-dependent translation may not be occurring. On the other hand, the eIF4E that is

present may be differentially restricted in its ability to bind the cap structure.

The 4E binding protein 1 (4E-BP1), a negative regulator of eIF4E, is often decreased in cancer cells (Ramirez-Valle, Braunstein et al. 2008). Analysis of 4E-BP1 protein levels via Western blotting showed there was no difference between 4E-BP1 levels in WI-38, MCF12A or MCF-7 cells (Figure 4.5B left). However, there was actually a 1.5 to 2.2 fold increase in the expression of 4E-BP1 in HMEC, MCF10A, and

HeLa S3 cells. The phosphorylation state of 4E-BP1 is integral to its activity with the hypophosphorylated 4E-BP1 able to bind 4E and inhibit cap-dependent translation.

Interestingly, there was a 1.5 to 3 fold increase of hypophosphorylated 4E-BP1 in all the cell lines compared to WI-38 cells (Figure 4.5B right). Taken together, these results do not support the hypothesis that cap structure accessibility is up-regulated in the immortalized cell lines over-expressing the Aurora A protein compared to the primary lines.

To definitively compare cap-dependent translation initiation between these cell lines we utilized a reporter assay. In vitro transcribed mRNA from monocistronic DNA containing the Photinus luciferase ORF, the β-globin 5’ leader and the SV40 poly A site was created. The β-globin 5’ leader was chosen because it is short (53 nt), unstructured, without an upstream ORF (uORF), and the β-globin mRNA is exclusively translated in a cap-dependent manner (Lockard and Lane 1978). The transcripts were capped with a methyl-7-guanosine (m7G) cap, poly (A) tailed, and transfected into each cell line. After

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Figure 4.5 A Gapdh eIF4E

B Gapdh

4E-BP1

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Figure 4.5 Changes in cap-dependent translation initiation do not correlate with Aurora A protein expression levels. (A) eIF4E protein levels were analyzed via western blotting with Gapdh as a loading control and normalized to the eIF4E expression level in WI-38 cells. n=3 + SD (B) 4E-BP1 protein levels were analyzed via western blotting with Gapdh as a loading control and normalized to the 4E-BP1 expression level in WI-38 cells (left).The percent of phosphorylated and hypophosphorylated 4E-BP1 in each cell line are shown (right). γ, β, and α represent the phosphorylation states of 4E-BP1 n=3 + SD (C) To measure global rates of cap-dependent transaltion in each cell line, translation of a Photinus luciferase reporter mRNA containing the β-globin 5’leader was transfected into the six cell lines. Luciferase activity was measured and the mRNA quantitated by qRT- PCR after 7 hrs. Shown is the ratio of luciferase activity to luciferase RNA. n=3 in triplicate + SD

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4 hr the cells were harvested and assayed for Photinus luciferase. The luciferase activity

from each cell line was compared to transcript levels quantitated using qRT-PCR to

normalize for transfection efficiency as well as mRNA stability. Translation of the

reporter was enhanced by 1.9 to 2.6 fold in all of the immortalized cell lines compared to

the normal cells (Figure 4.5C). Interestingly, MCF-7 cells, which do not over-express the

Aurora A protein, elicited the second largest increase of cap-dependent translation compared to WI-38 and HMEC cells (Figure 4.5C). This result indicates that other mechanisms aside from eIF4E and 4E-BP are contributing to enhanced cap-dependent translation. However, increased cap-dependent translation did not correlate with increased expression of Aurora A protein, thereby suggesting an alternate mechanism may be regulating translation of the Aurora A mRNA.

Aurora A protein expression level is unaffected by inhibiting cap-dependent translation initiation

To further determine the role of cap-dependent translation initiation in the

synthesis of the Aurora A protein, cap-dependent translation was inhibited using two different approaches. Initially eIF4E expression was knocked down. HeLa cells were transfected with a pool of siRNA (Dharmacon) targeting eIF4E mRNA or a nonsense siRNA for 48 hr. Quantification of Western blots showed that eIF4E protein expression

was reduced by nearly 70% (Figure 4.6A). Eukaryotic elongation factor 2 kinase

(eEF2K) expression in the eIF4E siRNA treated cells decreased by 57%, similar to previous observations (Dobson, Kube et al. 2008). In contrast, the level of Aurora A protein was equivalent in the eIF4E and nonsense siRNA conditions (Figure 4.6A).

As a second approach to modulate cap-dependent translation, HeLa cells were

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A B

Aurora A Aurora A eIF4E eIF4E eEF2K eEF2K Gapdh Gapdh mut 4E-BP1

Figure 4.6 Inhibiting cap-dependent translation initiation does not affect Aurora A protein expression. Two approaches were used to look at the effect downregulated cap- dependent translation would have on endogenous Auora A protein expression. (A) eIF4E, eEF2K (positive control) and Aurora A protein levels were determined by western blots of lysates from HeLa cells transfected with nonsense siRNA or siRNA targeting eIF4E for 48 hr. n=3, + SD (B) The same proteins were measure by western blots of lysates from HeLa cells transfected with a control vector or a plasmid encoding for mutant hypophosphorylated 4E-BP1 for 48 hr. n=3 +SD

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transfected with a DNA plasmid encoding a hypophosphorylated mutant of 4E-BP1 in which the main five phosphorylation sites are mutated rendering the protein non- phosphorylatable (generously provided by Dr. Davide Ruggero, University of California,

San Francisco) or a control vector (Paltag). The constitutively expressed hypophosphorylated 4E-BP1 should sequester eIF4E, thereby disrupting eIF-4F formation and inhibit cap-dependent translation (Gingras, Gygi et al. 1999). 48 hours after transfection, cells were harvested and protein levels were analyzed by Western blotting. eEF2K expression decreased by 75% in the presence of hypophosphorylated 4E-

BP1 (Figure 4.6B). eIF4E expression decreased by 53%, similar to previous results

(Dobson, Kube et al. 2008), indicating that the eIF4E mRNA is translated via a cap- dependent mechanism and a decrease in cap-dependent translation has occurred. On the other hand, the Aurora A protein level decreased by only 16% (Figure 3B). Taken together, these results show that synthesis of Aurora A kinase protein is relatively unaffected when cap-dependent translation is inhibited in HeLa cells indicating that an alternative mechanism may be contributing to the translation initiation of the Aurora A mRNA.

The Aurora A 5’ leader contains an IRES

Cap-dependent translation did not appear to be a significant mechanism for the synthesis of Aurora A protein in HeLa cells. This result indicated it may be translated in a cap-independent manner. To determine if the Aurora A 5’ leader had an IRES, it was inserted into the intercistronic region of a dicistronic luciferase construct coding for

Renilla and Photinus luciferase in the first and second cistrons, respectively (Stoneley,

Paulin et al. 1998). The β-globin 5’ leader, which does not contain an IRES, was used as

140 a negative control. Two viral IRESes, the encephalomyocarditis virus (EMCV) IRES and the IRES in the intergenic region of the cricket paralysis virus (CrPV) were chosen as positive controls (Jang, Davies et al. 1989; Jan and Sarnow 2002). The constructs were in vitro transcribed to eliminate the possibility of cryptic promoter activity or alternative splicing (Thompson 2012; Van Eden, Byrd et al. 2004). The resulting dicistronic transcripts were transfected into HeLa cells. After 7 hr the cells were harvested and assayed for Renilla and Photinus luciferase. The Photinus:Renilla (P:R) luciferase ratio obtained from the β-globin dicistronic construct was normalized to one. Consequently, a ratio above one would indicate IRES activity. The P:R ratio obtained from the dicistronic luciferase mRNA containing the Aurora A 5’ leader was 5 fold higher than that obtained from the dicistronic mRNA containing the β-globin 5’ leader (Figure 4.7A). This ratio was similar to the one obtained from the mRNA containing the CrPV IRES, but less than the 20 fold increase in the P:R ratio from the mRNA containing the EMCV IRES. These results indicated that the Aurora A 5’ leader contains an IRES which exhibits activity similar to the CrPV IRES in HeLa cells.

To further validate the presence of an IRES in the Aurora A 5’ leader, in vitro transcribed monocistronic mRNA containing the Photinus luciferase ORF and the β- globin or Aurora A 5’ leader was translated in rabbit reticulocyte lysate. Cap-dependent translation was inhibited by adding increasing amounts of cap analog to compete with the m7G cap. Luciferase activity measured from the β-globin construct decreased by 70% in the presence of 100μM of cap analog while luciferase activity from the Aurora A construct was relatively unchanged (Figure 4.7B). This result demonstrated that the

Aurora A 5’ leader initiates translation independently of the cap structure and supports

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A B

Figure 4.7 The 5’ leader of the Aurora A mRNA contains an IRES (A) Dicistronic luciferase mRNA containing the 5’ leader of β-globin (negative control) or Aurora A and the CrPV or EMCV IRES (positive controls) were transfected individually into HeLa cells. Luciferase activity is shown as the ratio of Photinus luciferase to Renilla luciferase (P:R) and is normalized to that obtained from the dicistronic mRNA containing the β- globin 5’ leader. n=3 in triplicate + SD (B) Monocistronic Photinus luciferase mRNA containing the β-globin or Aurora A 5’ leader were translated in rabbit reticulocyte lysate in the presence of increasing concentrations of cap analog. The initial level of Photinus luciferase activity from each monocistronic mRNA was normalized to 100. n=3 + SD (C) Cell cycle progression following the release of a double thymidine block in HeLa cells was confirmed by flow cytometry analysis (left). HeLa cells transfected with dicistronic luciferase mRNA containing the β-globin and Aurora A 5’ leaders were synchronized in G1/S with a double thymidine block and released (0hrs). Luciferase activity is shown as the ratio of Photinus luciferase to Renilla luciferase (P:R) and is normalized to that obtained from the dicistronic mRNA containing the β-globin 5’ leader at the 0 time point (right). IRES activity increased as cells enter G2/M (6 and 8 hrs). n=3 in triplicate + SDs

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the hypothesis that it contains an IRES.

Expression levels of both Aurora A mRNA and Aurora A protein peak during the

G2/M phase of the cell cycle (Honda, Mihara et al. 2000; Tanaka, Ueda et al. 2002). This

temporal expression coincides with reports indicating that IRES activity is regulated

through the cell cycle and peaks at G2/M (Tinton, Schepens et al. 2005; Lewis and

Holcik 2008). To determine if the Aurora A IRES is regulated by the cell cycle, HeLa

cells were synchronized by a double thymidine block. During the last thymidine block the

cells were transfected with in vitro transcribed dicistronic mRNA containing either the β- globin or Aurora A 5’ leader in the intercistronic region. Cells were harvested between 0 to 8 hours following release from the double thymidine block into normal growth medium with the total transfection time being 11 hours for all cells. FACs analysis showed the majority of cells were synchronized in G1/S and proceeded through the cell cycle, entering G2/M at approximately 6 to 8 hrs after release (Figure 4.7C left). The P:R ratio obtained from the β-globin construct at the time of thymidine release was set to one and did not change during the phases of the cell cycle. On the other hand, immediately after thymidine release the Aurora A P:R ratio was 4.2 fold higher than that obtained with

β-globin and increased with time after the release peaking 8 hours later with a P:R ratio of 6.4 (Figure 4.7C right). This result indicates that the Aurora A IRES is active throughout the cell cycle but peaks during the same portion of the cell cycle in which translation of the endogenous Aurora A mRNA does – G2/M.

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Aurora A IRES activity is increased in the cell lines that over-express Aurora A

protein

To determine if Aurora A IRES activity correlated with Aurora A protein

expression levels, dicistronic mRNA containing the Aurora A or β-globin 5’leaders was

transfected into all six cell lines. After 7 hr the cells were harvested and assayed for

Renilla and Photinus luciferase. The P:R ratio for the mRNA containing the Aurora A 5’

leader was at least two-fold higher than the control in all cell lines indicating the Aurora

A IRES is operative in all cell lines (Figure 4.8A). Moreover, the Aurora A P:R ratio

was highest in the cell lines that also express the highest levels of Aurora A protein,

MCF10A, MCF12A, and HeLa S3 (Figure 4.8A). These results show a positive

correlation between Aurora A protein expression and Aurora A IRES activity. This

correlation supports the hypothesis that IRES-dependent translation is contributing to the

over-expression of the Aurora A protein observed in the subset of cell lines.

All eukaryotic transcripts contain a methyl-7-guanosine cap. Accordingly, translation of the Aurora A mRNA may be initiated through the cap structure and/or the

IRES. To measure the potential usage of the Aurora A IRES in a monocistronic mRNA, the β-globin or Aurora A 5’ leader were placed upstream of the Photinus luciferase ORF

and in vitro transcribed. The transcripts were capped with an m7GpppG (m7G cap) or

ApppG cap (A cap) and poly (A) tailed (Figure 4.9A). The A cap is not recognized by

eIF4E preventing cap-dependent translation initiation of the mRNA. In addition, the poly

(A) specific 3’exonuclease PARN does not recognize the A cap, thereby inhibiting

deadenylation and preventing both 5’ and 3’ exonucleolytic mRNA decay (Bergamini,

Preiss et al. 2000; Dehlin, Wormington et al. 2000). The mRNA was co-transfected into

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Figure 4.8 Aurora A IRES activity is increased in the subset of immortalized cell lines Dicistronic mRNA containing the β-globin and Aurora 5’ leaders were transfected into each cell line. The P:R ratio obtained from the β-globin construct from each cell line was set to one. The P:R ratio from the Aurora A construct was normalized to β-globin. n=3 in triplicate + SD

145 each cell line with a m7G capped and poly (A) tailed mRNA containing the humanized

Renilla luciferase ORF to normalize for transfection efficiency. For each cell line, the

P:R ratio obtained from the m7G cap Photinus construct was set to 100. The P:R ratio obtained from the A cap Photinus luciferase mRNA was compared to the P:R ratio obtained from the corresponding m7G cap Photinus luciferase constructs. The A cap reporter mRNA containing the β-globin leader was poorly translated (5 to 16% of the m7G cap P:R ratio) (Figure 4.9B). This result demonstrated that the translation of the mRNA containing the β-globin 5’ leader was dependent on the presence of the m7G cap structure. In the WI-38 and HMEC cells, translation of the A cap mRNA containing the

Aurora A 5’ leader was higher than the mRNA with the β-globin leader. This result indicates that the Aurora A 5’ leader was initiating cap-independent translation, although it was only approximately 25% of that obtained by a m7G cap mRNA containing the

Aurora A 5’ leader (Figure 4.9C). On the other hand, the A cap P:R ratio from the Aurora

A construct was considerably higher in the cell lines that over-express the Aurora A protein (MCF10A, MCF12A, and HeLa S3). Remarkably, in the MCF12A cells Photinus luciferase activity from the A cap mRNA was 95% of that obtained from the m7G cap

Aurora A mRNA (Figure 4.9). These results suggest cap-dependent translation is most likely a contributing mechanism for Aurora A protein synthesis in the low expressing lines, but IRES-dependent translation is the predominant mechanism in the Aurora A over-expressing lines.

To determine if IRES activity in general was upregulated in the Aurora A over- expressing cell lines, the experiment was repeated using transcripts containing the 5’

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Figure 4.9 A

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Figure 4.9 Translation initiation of the Aurora A 5’ leader of an Apppg capped transcript is enhanced in Aurora A over-expressing cells (A) Schematic representation of cotransfections of an ApppG or m7GpppG capped monocistronic Photinus luciferase mRNA containing the β-globin (negative control), Aurora A or FMR1 (specificity control) 5’ leaders with an m7GpppG capped Renilla luciferase mRNA to control for transfection efficiency. (B) Normalized luciferase activity obtained from the ApppG capped Photinus constructs are represented as a percentage of the normalized luciferase activity obtained from the m7GpppG capped Photinus construct for the β-globin 5’ leader. (C) Normalized luciferase activity obtained from the ApppG capped Photinus constructs are represented as a percentage of the normalized luciferase activity obtained from the m7GpppG capped Photinus construct for the Aurora A 5’leader. (D) Normalized luciferase activity obtained from the ApppG capped Photinus constructs are represented as a percentage of the normalized luciferase activity obtained from the m7GpppG capped Photinus construct for the FMR1 5’ leader. Potential IRES activity from the FMR1 5’ leader does not correlate with Aurora A protein expression. p values calculated by Student t test, n=3 in triplicate + SD

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leader of the FMR1 mRNA, which contains an IRES (Chiang, Carpenter et al. 2001;

Dobson, Kube et al. 2008). Internal initiation mediated by the FMR1 IRES varied

between the cell lines but the activity did not correlate with that observed from the

Aurora A IRES (Figure 4.9D). FMR1 IRES activity was similar in WI-38, HMEC,

MCF12A and MCF-7 cell lines, elevated in MCF10A, and decreased in HeLa S3 cells.

This result indicated that activity of all IRESes is not enhanced in the Aurora A over-

expressing cell lines.

Further correlation between Aurora A IRES activity and protein expression

To determine if the correlation between Aurora A IRES activity and protein

expression extends to other cell lines, we performed the same assay with three lines from

the 21T cell line series (21PT, 21NT, and 21MT2). These cell lines were derived from a

single patient diagnosed with infiltrating and intraductal mammary carcinoma and are

often used as an in vitro model for cancer progression. The non-tumorigenic 21PT and

the tumorigenic 21NT cell lines were derived from a primary tumor. The 21MT2 line was

derived from a metastasic tumor (Band and Sager 1989; Band, Zajchowski et al. 1990;

Band 1991). All three cell lines over-express Aurora A protein (Figure 4.10A), yet

mRNA levels (Figure 4.10B) and protein half-life (2.8-3.1 hrs) were equivalent to the

normal cell lines (Figure 4.11). The elevated Aurora A protein/mRNA ratio indicated an

increase in Aurora A translation (Figure 4.10C). The A/m7G cap monocistronic transfection experiment demonstrated a high level of Aurora A IRES usage. The percentage of A cap mediated translation to that obtained FROM the m7G cap with the

Aurora a 5’ leader ranged from 60% (21PT) to 83-85% (21MT2 and 21NT respectively)

(Figure 4.12). These results are similar to what was seen with MCF12A, MCF10A and

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A Aurora A Gapdh

Figure 4.10 Additional cell lines over-express Aurora A protein (A) Endogenous protein levels in four more cell lines were analyzed via Western blotting with Gapdh as a loading control and normalized to the Aurora A expression level in WI-38 cells. n=3 + SD (B) Total RNA was isolated from the four cell lines and analyzed via qRT-PCR with Gapdh as a reference target. Results were normalized to the Aurora A mRNA level in WI-38 cells. n=3 + SD (C) The ratio of the normalized Aurora A protein levels to normalized Aurora A mRNA levels are shown.

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Figure 4.11 Protein stabilty is similar between the additional lines and low Aurora A expressing cells Quantitation from Western blotting of Aurora A protein expression levels from the four cell lines treated for 0 to 12.5 hours with cycloheximide. Expression level of Aurora A protein in the untreated cells (0 hr) was normalized to 100. n=3 + SD

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Figure 4.12 Additional breast epithelial cell lines demonstrate a correlation between Aurora A IRES activity and Aurora A protein expression Normalized luciferase activity from the ApppG capped Photinus constructs are represented as a percentage of the normalized luciferase activity obtained from the m7GpppG capped Photinus construct for the β-globin 5’ leaders (top) and the Aurora A 5’leader (bottom). p values calculated by Student t test, n=3 in triplicate + SD

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HeLa S3 cells.

To determine if increased proliferative activity contributed to alterations in

Aurora A IRES activity, this assay was performed in a HMEC cell line that ectopically expresses telomerase (HMEC-t); a cellular process that prevents replicative cellular aging. Over-expressing telomerase did not alter Aurora A protein levels, mRNA levels, or protein stability (Figures 4.10A-C and 4.11). In addition, the Acap P:R ratio exhibited by these cells was similar to that obtained from WI-38 and HMEC cells (Figure 4.12).

These results demonstrate that IRES-dependent translation initiation mediated by the

Aurora A 5’leader is utilized to a greater extent in cells over-expressing the Aurora A protein. Simply extending proliferative activity does not alter Aurora A IRES activity or protein levels. These results further support the hypothesis that there is enhanced IRES- dependent translation of the Aurora A mRNA resulting in an increase of Aurora A kinase expression, which I propose predisposes the cell to immortalization and tumorigenesis.

Discussion

In summary, I have identified an IRES situated in the 5’ leader of the human

Aurora A mRNA. In an examination of multiple cell lines, IRES activity was the only mechanism that correlated with Aurora A protein expression. Moreover, this mechanism appears to be upregulated early during cancer development and remains elevated as cell transformation advances indicating that targeting this mechanism may be beneficial for multiple stages of cancer progression.

Over-expression of the Aurora A kinase is observed in a broad range of malignancies including breast, brain and pancreatic tumors (Sen, Zhou et al. 1997;

Bischoff, Anderson et al. 1998; Gritsko, Coppola et al. 2003; Jeng, Peng et al. 2004;

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Neben, Korshunov et al. 2004; Hata, Furukawa et al. 2005). Misregulation of its expression is proposed to be both an early event in the immortalization of the cell as well as a contributor to the epithelial to mesenchymal transition (EMT) (Wan, Long et al.

2008; Tseng, Lee et al. 2009). In this study, my goal was to identify mechanism(s) contributing to Aurora A protein over-expression. To this end I chose six cell lines, which included primary, immortalized and tumorigenic cell types. They were categorized as either high or low Aurora A protein expressing cells. Transcription/mRNA stability, protein stability, nor cap-dependent translation could account for enhanced levels of

Aurora A protein in the high expressing lines. On the other hand, I identified an IRES in the Aurora A 5’leader and IRES activity strongly correlated with Aurora A protein expression.

Determining the potential “IRES usage” of the Aurora A 5’ leader

Utilizing RNA dicistronic luciferase constructs, Aurora A IRES activity was shown to correlate with Aurora A protein expression. However, this assay does not measure the contribution of the IRES in an m7G capped monocistronic mRNA, the state in which the Aurora A mRNA is present. It has been suggested that eukaryotic IRESes initiate translation at a considerably reduced rate compared to m7G cap-dependent initiation (Merrick 2004; Kozak 2005). Thus, even if IRES activity is enhanced in a subset of cell lines the overall increase may not be physiologically significant. To address this issue, I created monocistronic mRNA containing the Aurora A IRES with an ApppG or m7G cap. These RNAs would permit comparison between translation initiated in a cap-independent manner to translation mediated by an m7G cap and an IRES (Bergamini,

Preiss et al. 2000). The resulting Acap/m7G cap ratio I termed ‘IRES usage’. In WI-38

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and HMEC cells, A-capped translation of the RNA containing the Aurora 5’ leader was

less than 25% of that obtained from an m7G capped mRNA (see Figure 4.9C). This result

indicated that cap-dependent translation is likely the predominant mechanism. However,

transfection into the other cell lines yielded dramatically different results. In MCF12A

cells, translation of the mRNA was similar irrespective of the cap structure (see Figure

4.9C). This is one of the first examples whereby a eukaryotic IRES initiates translation at a rate similar to an m7G capped transcript. We interpret this result as demonstrating that

IRES-dependent translation is elevated and is the principal mechanism utilized to initiate translation of the m7G capped mRNAs. On the other hand, reduced cap-dependent translation without any concomitant alteration in IRES activity could yield a similar result. To differentiate between these two explanations, I examined cap-dependent translation of a monocistronic mRNA and found that it was relatively similar between the four immortalized lines and actually higher than the two primary cell lines (see Figure

4.5C). Accordingly, these results indicate an apparent switch from low level cap- dependent translation of the Aurora A mRNA in normal, finite lifespan cells to increased

IRES-dependent translation in immortalized cells prior to malignant transformation.

Identifying the mechanism(s) that play a role in this switch could be crucial to

understanding oncogenesis mediated by Aurora A kinase over-expression and possibly of

other oncogenes which are translated in an IRES-dependent manner.

Additional cell lines reinforced the positive correlation between IRES usage and

Aurora A protein expression. The 21T series exhibited both elevated Aurora A protein levels and IRES activity; while Aurora mRNA and protein half-life was similar to the finite cell lines (see Figures 4.10, 4.11, and 4.12). This group of cells included

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immortalized, but nontumorigenic (21PT), tumorigenic (21NT), and finally metastatic

(21MT2). These results are consistent with previous reports suggesting enhanced Aurora

A expression contributes to immortalization and continues through the epithelial-

mesenchymal transition (Wan, Long et al. 2008; Tseng, Lee et al. 2009).

A novel target for repressing Aurora A protein expression in cancer

Internal initiation of translation has been invoked as a mechanism involved in

carcinogenesis (reviewed in (Holcik 2004)). Multiple mRNAs encoding proteins

contributing to cell proliferation (FGF2, PDGF2), cell cycle (PITSLRE p58), cell

death/survival (Bcl-X, Apaf1), and tumor development (p53, c-myc, c-jun) contain

IRESes (Stoneley, Paulin et al. 1998; van der Velden and Thomas 1999; Coldwell,

Mitchell et al. 2000; Cornelis, Bruynooghe et al. 2000; Sehgal, Briggs et al. 2000;

Sherrill, Byrd et al. 2004; Yang, Halaby et al. 2006). Misregulating IRES-dependent

translation contributes to cancer progression through variable means. For example, in the

disease X-Linked Dyskeratosis Congenita, mutations in the dyskerin gene reduce

pseudouridylation of rRNA, which inhibits IRES-dependent translation of tumor

suppressors (p53, p27) and apoptotic factors (Bcl-X, XIAP) predisposing individuals to

cancer (Bellodi, Kopmar et al. 2010; Montanaro, Calienni et al. 2010; Yoon, Peng et al.

2006). Alternatively, the low oxygen environment in the center of solid tumors increases

IRES-dependent translation of the VEGF mRNA, which in turn promotes angiogenesis and tumor growth (Braunstein, Karpisheva et al. 2007). In the present study, I found that the Aurora A IRES is regulated through the cell cycle and by cell type. As a first step towards identifying the mechanism, it would be of interest to determine whether other

IRESes that are utilized during the G2/M phase of the cell cycle or are present in the 5’

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leader of mRNA encoding other oncogenes exhibit IRES usage patterns similar to Aurora

The mechanism regulating the Aurora A IRES is unknown. For eukaryotic

IRESes, the rate-limiting step is proposed to be the expression level of non-canonical

proteins termed IRES-transacting factors (ITAFs) (reviewed in (Hellen and Sarnow

2001)). These are RNA binding proteins that aid in the recruitment of the translational

machinery and/or alter the RNA secondary structure, which in turn promotes binding of

the translation complex. ITAF mis-expression can alter translation of cancer-related

mRNAs. For example, murine double minute (MDM2) is an oncoprotein that binds the

IRES in the mRNA encoding the X-linked inhibitor of apoptosis protein (XIAP).

Increased XIAP expression in the MDM2 over-expressing cells leads to a resistance to radiation-induced apoptosis (Gu, Zhu et al. 2009). Alternatively, a loss of two other

ITAFs, TCP80 and RHA diminishes p53 IRES activity and protein expression; promoting cell survival in response to DNA damage (Halaby, Hibma et al. 2008). Presumably, there are ITAFs whose increased expression is responsible for the enhanced Aurora A IRES activity. Since there is no in vivo assay to quantify Aurora A IRES activity in normal/immortalized cells, the level of these regulatory proteins would be a useful biomarker and provide a novel drug target to modulate Aurora A IRES activity in cancer cells. Two ITAFs known to be expressed in G2/M are polypyrimidine-tract binding protein (PTB) and upstream of n-ras (Unr). They both bind the PISTRLE p58 IRES and regulate the G2/M specific expression of the PISTLRE p58 protein (Ohno, Shibayama et al. 2011; Tinton, Schepens et al. 2005). They can also regulate IRESes during other phases of the cell cycle, such as the Apaf-1 IRES during G1/M. However, knocking

157 down Unr did not affect Aurora A IRES activity (unpublished observations) and there does not appear to be any potential PTB binding sites in the Aurora A 5’ leader.

Consequently, there are likely to be additional ITAFs that regulate the Aurora A and possibly other mitotic IRESes. Indeed, it would be of interest to determine whether the

Aurora A IRES represents another subset of G2/M functionally related IRESes.

Current anti-cancer drugs target Aurora A kinase activity since its inhibition leads to formation of a monopolar spindle and cell death (Lee, Frolov et al. 2006). However, it has been difficult to design reagents that exhibit specificity for the ATP pocket of the

Aurora A kinase (Mountzios, Terpos et al. 2008; Kitzen, de Jonge et al. 2010). Moreover, over-expressing a kinase dead mutant of Aurora A can still contribute to cellular immortalization (Dutertre, Descamps et al. 2002). Our results indicate that cap-dependent translation is the principal initiation mechanism in primary cells, whereas IRES- dependent translation is utilized to over-express Aurora A kinase in the immortalized cells. Consequently, designing reagents targeting the IRES would inhibit Aurora A protein expression primarily in cancer cells.

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CHAPTER V

TRANSLATIONAL REGULATION

OF AURORA A KINASE EXPRESSION IN CANCER

Introduction

Aurora A kinase over-expression is implicated as a contributing factor in cellular

immortalization. Indeed, a rat mammary tumor model study indicates that alterations of

Aurora A expression are early events during mammary tumor development (Goepfert,

Adigun et al. 2002), suggesting that Aurora A over-expression plays a pivotal role in

transformation. The molecular mechanism(s) by which Aurora A induces cell

transformation remains elusive. In addition, what initially triggers over-expression of

Aurora A is still unknown.

Enhanced expression of Aurora A protein in tumors is reportedly due to a

concomitant increase in Aurora A mRNA owing to gene amplification and/or increased

transcription (Tanner, Tirkkonen et al. 1994; Tanner, Tirkkonen et al. 1995; Bischoff,

Anderson et al. 1998; Zhou, Kuang et al. 1998; Tanner, Grenman et al. 2000). However,

there are examples in many cancers whereby increased Aurora A protein expression is

not accompanied by changes in mRNA levels (Lai, Tseng et al. 2010; Gritsko, Coppola et

al. 2003; Jeng, Peng et al. 2004). These results suggest that post-transcriptional processes

including enhanced protein synthesis and/or protein stability are also likely contributing to the increased Aurora A kinase levels.

Protein synthesis is mainly regulated at the step of translation initiation. There are

two mechanisms of initiation utilized by eukaryotic cells, cap-dependent and IRES-

dependent translation initiation. I have found an Internal Ribosomal Entry Site (IRES) in

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the 5’ leader of the Aurora A mRNA (Chapter IV). Interestingly, increased IRES activity

correlates with increased protein expression in three immortalized but non-tumorigenic

breast epithelial lines (MCF10A, MCF12A, and 21 PT) compared to normal, finite

lifespan breast epithelial cells (HMECs) (see Figure 4.1 and 4.12). This finding suggests

Aurora A IRES activity may contribute to Aurora A over-expression leading to

immortalization. But what events lead to increased Aurora A IRES activity is unknown.

Cellular IRESes are regulated by cis-elements and IRES-trans-acting factors or

ITAFs. Cis- elements that mediate cap-independent translation initiation of eukarytic

IRESes typically range from 7-50 nt. I have identified such sequences in the FMR1

leader (see Figure 3.4) as well as in the TrkB IRES (Dobson, Minic et al. 2005).

However, the cis-elements of eukaryotic IRESes are diversified with no primary

sequence similarities to define a consensus sequence. The sequence element that is most

commonly seen in cellular IRESes is a polypyrimidine tract. This motif recruits the

polypyrimdine-tract binding protein (PTB) which can recruit the ribosome to the IRES

element (Spriggs, Mitchell et al. 2005). In addition to sequence, some cellular IRESes

have been shown to recruit the translation machinery to the mRNA via secondary

structural elements. Indeed, the polypyrimidine motif is often part of a hairpin. The 5’

leader of the mouse potassium channel mKv1.4 contains an IRES that combines a

polypyrimidine tract, a pseudoknot, and stem loop formations to recruit the translation

machinery (Jang, Leong et al. 2004). Although cis-elements vary, most cellular IRESes

are thought to require at least one non-canonical factor for internal initiation of

translation.

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Identifying ITAFs is very important to the overall understanding of the

mechanism by which a cellular IRES initiates translation. After recruitment to the mRNA

via cis-elements, these non-canonical RNA-binding proteins either alter conformation of

the mRNA or stabilize a specific IRES conformation thus enabling recruitment of other

initiating factors including the ribosome (Meng, Jackson et al.). Unr is an ITAF that

regulates activity of G2/M specific IRESes. This ITAF binds 11-14 nt long purine rich

sequences that are predominantly adenosines (Triqueneaux, Velten et al. 1999). Unr

expression is upregulated during mitosis and contributes to the enhancement of IRES-

dependent translation of the p58 PITSLRE kinase during the G2/M phase of the cell cycle

(Tinton, Schepens et al. 2005). Interestingly, the unr mRNA is translated via an IRES that

is negatively regulated by PTB (Cornelis, Bruynooghe et al. 2000).

Signaling pathways regulate protein synthesis in response to varying cellular

conditions. Cap-dependent translation can be globally upregulated by the

PI3/AKT/mTOR pathway via phosphorylation of the 4E-BPs in response to cellular

signals such as growth factors (Fadden, Haystead et al. 1997; Heesom, Avison et al.

1998). Other pathways including mitogen-activated protein kinase (MAPK) signaling has

been implicated in regulating cap-dependent translation. Activation of ERK and RSK

leads to enhanced mTORC1 activity thereby upregulating cap-dependent translation

(Goetz, Everson et al.). These pathways also regulate translation via the many phosphorylation sites on eukaryotic initiation factors that control interactions with both proteins and RNA (Traugh, Tahara et al. 1976; Duncan and Hershey 1985; Duncan,

Milburn et al. 1987). With the exception of eIF4E, IRES-dependent translation requires

these same canonical eIFs, indicating this mechanism is also affected by the same

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pathways. For example, both cyclin D1 and c-myc IRES actvity can be regulated by AKT

activity. Activity of these IRESes is further enhanced by rapamycin, a drug that inhibits

cap-dependent translation, through a p38 MAPK- and ERK-dependent pathway (Shi,

Sharma et al. 2005). However, no general signaling pathway regulating IRES-dependent translation has been identified.

In Chapter IV I cloned the known Aurora A 5’ leader at that time (Genbank

XM_114165). Since then additional leaders have been added to Genbank. These variants all encode the same Aurora A protein but each contains a unique 5’ leader. Alternative splicing of oncogenic kinases can contribute to cancer development (Druillennec, Dorard et al. 2012). For example, several studies have report expression of ErbB2 isoforms that are present in both normal and malignant breast cells. The in-frame deletion of 16 amino acids in the juxtamembrane domain due to exon 16 splicing results in formation of

ΔErbB2 which has greater transforming ability than wild type ErbB2 (Kwong and Hung

1998). Alternative splicing of FGFR2 also appears to be implicated in cancer. FGFR2 exon switching from the IIIb to the IIIc isoform has been observed during epithelial cell tumor progression (Yan, Fukabori et al. 1993). However, unlike these examples where splicing results in protein synthesis of an isoform, the Aurora A splice variants all encode the same protein. It is not clear what physiological roles these variants play in tumorigenesis or under nonpathological conditions.

The goal of this study was to identify regulators of the Aurora A IRES. But first I needed to determine which 5’ UTR splice variants of the Aurora A mRNA were present in the cell lines used in the previous study (WI-38, HMECs, MCF10A, MCF12A, MCF-7 and HeLa S3). I identified a total of 9 variants that were present in each of the lines at

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similar levels. Six out of nine variants could internally initiate translation and four of

those six demonstrated elevated IRES activity in Aurora A over-expressing breast epithelial cell lines (MCF10A and MCF12A) versus low Aurora A expressing breast epithelial cell lines (MCF-7 and HMECs). Dissecting the variants yielded three presumably independent IRESes localized to exons Ib, II, and IIa of the 5’leader of the

Aurora A gene. The exon Ib IRES is active in primary as well as immortalized cell lines.

In contrast, exon II and IIa IRES activity is enhanced in lines that over-express Aurora A protein.

To identify signaling pathways that regulate activity of the Aurora A IRESes I performed a human kinase/phosphatase siRNA library screen. Results from this screen along with phospho-proteome arrays led me to hypothesize that ligand-bound growth factor receptors activate the MAPK/ERK pathway as well as differentially alter specific

AKT phosphorylation sites. Together they lead to increased translation of the exon II but not the exon IIa or exon Ib IRES in Aurora A over-expressing cell lines. I suggest that upregulation of these pathways leads to enhanced Aurora A exon II IRES activity and protein expression, which in turn contribute to cellular immortalization and possibly transformation.

Results

Identification of nine alternatively spliced 5’ leaders of the Aurora A mRNA

A total of six alternatively spliced Aurora A transcripts, differing only in their 5’ leaders have been found in various types of tumors (Lai, Tseng et al. 2010; Shin, Lee et al. 2000). To determine which leaders were present in the original cell lines used to identify IRES activity from one of these variants, I performed PCR with cDNA libraries

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derived from each line using primers designed against the 5’end of exon I and the ORF.

These experiments constantly failed to produce products.

There are two potential transcription start sites (TSS) (blue arrows Figure 5.1) for the Aurora A gene (Lai, Tseng et al. 2010; Sen, Zhou et al. 1997). PCR was repeated with a new set of primers (red arrows Figure 5.1) -the original reverse primer and new forward

primer designed immediately downstream of the second TSS. A total of nine 5’ leaders

were identified in all the cell lines tested using this second primer set (Figure 5.1). Along

with the original Aurora A leader, they include 5’ end truncated versions of 5 out of the 6

Genbank variants. Truncated variant 2 (tV2) is the leader discovered in mammalian cells

when Aurora A was known as STK15/BTAK or breast tumor amplified kinase (Sen,

Zhou et al. 1997; Zhou, Kuang et al. 1998). Along with the truncated variants 3, 4, 5 and

6, I discover three new variants that I named Unique A, B and C (UA,UB and UC)

(Figure 5.1).

Three independent IRES elements reside in exons Ib, II, and IIa of the 5’ leader of

the Aurora A gene

The original Aurora A 5’ leader of this study (Aurora A in Figure 5.1) was

previously found to initiate translation in a cap-independent manner. This leader is

comprised of exons I, Ia, Ib, and II. To determine what region(s) was contributing to

IRES activity, each individual exon was cloned into a monocistronic reporter vector

encoding Photinus luciferase. RNA constructs containing the β-globin leader as a

negative control, Aurora A 5’ leader, Aurora A exons and EMVC IRES as a positive

control were derived by in vitro transcription and were capped with an ApppG cap analog

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Figure 5.1 Schematic diagram of the 5’ UTR of the Aurora A gene and the alternate splicing variants of the 5’ leader of the Aurora A mRNA The 5’ untranslated region of the Aurora A gene is composed of 5 exons (exons I, Ia, Ib, II and IIa). These exons can be alternatively spliced to create Aurora A transcripts that vary only in the 5’ leader. Nine different Aurora A 5’ leaders were identified in all of the following cell lines: WI-38, HMEC, MCF10A, MCF12A, MCF-7 and HeLa S3. They were found by PCR using primers targeting the 3’ end of exon I and the ORF (red arrows). The PCR products were cloned into Topo TA vectors and sequence verified. No products were obtained with a 5’ primer targeting the 5’ end of exon I indicating these cell lines utilized the second of the two transcription start site (blue arrows) in the 5’UTR of the Aurora A gene.

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and poly (A) tailed (as previously described, see Chapter IV). The RNA constructs were

transfected into the four breast epithelial cell lines utilized in my previous work. Two of

these lines, the human mammary epithelial cells (HMECs)- a primary cell line with a

finite lifespan- and MCF-7 cells- an immortalized, tumorigenic cell line-had been shown

to exhibit similar levels of Aurora A protein (Figure 4.1). The other two cell lines

MCF10A and MCF12A-both immortalized, but non-tumorigenic- expressed high levels

of Aurora A protein compared to HMECs and MCF-7 cells (Figure 4.1).

After four hours, half of the cells from each transfection were collected to

measure Photinus luciferase activity and the other half was used to measure transcript

levels by qRT-PCR (Figure 5.2). Photinus luciferase activity was compared to transcript

levels to normalize for both transfection efficiency and mRNA stability. The Photinus luciferase activity to mRNA ratio obtained from the β-globin construct in HMEC cells was set to one and was used to normalize the ratios obtained from the β-globin construct as well as the other constructs in all cell lines (Figure 5.3). As before, the Aurora A IRES exhibits IRES activity in all cell lines but is increased in the over-expressing cells. On the other hand exon I did not exhibit any IRES activity. Surprisingly, IRES activity was observed from the three other exons suggesting that exons Ib, II and IIa had potential

IRES elements. IRES activity from exon Ib was high in all four cell lines. Compared to

β-globin in HMECs, exon Ib activity was 8 fold higher in HMECs, 4.5-5 fold higher in both MCF-7 and MCF12A HMECs, and 11 fold higher in MCF10A cells. Unlike exon

Ib, IRES activity from exon II and exon IIa was higher in the over-expressing lines. Exon

II in both MCF12A and MCF10A cells demonstrated a 2 fold increase in activity

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Figure 5.2 Schematic representation of ApppG capped single luciferase assay Individual exons or 5’ leaders are cloned into a monocistronic reporter vector encoding Photinus luciferase. RNA constructs are derived by in vitro transcription and capped with an ApppG cap analog and poly (A) tailed. The RNA constructs are transfected in cells. After four hours the cells are trypsinized and harvested. Half of the cells are lysed and Photinus luciferase activity is measure by a single luciferase assay using a luminometer. The second half of the cells are exposed to TRIzol and total RNA is extracted. cDNA libraries are derived from the exact amount of total RNA from each sample. Photinus luciferase transcript levels are quantified from these libraries by qRT- PCR. Gapdh transcript levels are also quantified by qRT-PCR and used to normalize Photinus transcript concentrations. A ratio between Photinus luciferase activity and normalized Photinus transcript levels represents the amount of translation per mRNA for each construct. This method normalizes for both transfection efficiency as well as mRNA stability. It allows for direct comparisons between the translational activities of different constructs as well as between the same construct in different cell lines.

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Figure 5.3 Exons Ib, II and IIa contain IRES elements To compare IRES-dependent translation between the low Aurora A expressing (HMEC and MCF-7) and high Aurora A expressing (MCF10A and MCF12A) cell lines, reporter constructs containing the β- globin or Aurora A 5’ leader, Aurora A exons or the EMCV IRES were in vitro transcribed then capped with an ApppG cap analog and poly (A) tailed. The RNA constructs were transfected into each cell line as previously describe (Figure 5.2). The Photinus luciferase activity to mRNA ratio obtained from the β-globin construct in HMEC cells was set to one and was used to normalize the ratios obtained from the β- globin construct and the other constructs in all cell lines. Any ratio greater than one indicates IRES activity. The results show exons Ib, II and IIa contain IRES elements and IRES activity from exons II and IIa is greater in the high expressing cell lines (MCF12A and MCF10A). These results suggest that the Aurora A IRES elements are differentially regulated. n=3 + SD

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compared to HMECs and was 4 fold higher than MCF-7 cells. Exon IIa activity was similar between HMEC and MCF-7 cells but was 2 fold higher in MCF12A cells and

5 fold higher in MCF10A cells. Interesting, as demonstrated by activity from the Aurora

A leader, IRES activity from exon Ib seen in in HMEC and MCF-7 cells is not evident when in combination with exon II. There is also a decrease in activity from exon Ib in

MCF10A cells compared to the Aurora A leader. These results suggest a potential change in secondary structure occurs when these elements are within the same leader, perhaps impeding access to a cis-element in exon Ib.

Six Aurora A variants initiate translation cap-independently

To determine which leaders had IRESes and to compare translation rates between the four breast cell lines, I utilized the Acap monocistronic assay (Figure 5.2). With the

help of two student workers under my supervision (Jay Yao from Rice University and

Jeanette Tucker from University of Texas–MD Anderson Cancer Center) all nine 5’

leaders were cloned into the monocistronic Photinus Luciferase reporter. RNA constructs

containing the Aurora A leaders, the β-globin 5’ leader as a negative control, and the

EMCV IRES as a positive control were derived by in vitro transcription and capped with

an ApppG cap analog and poly (A) tailed. The RNA constructs were transfected into the

four breast epithelial cell lines (Figure 5.4). Four hours later half of the cells from each

transfection were collected to measure Photinus luciferase activity and the other half

were used to measure transcript levels by qRT-PCR. Photinus luciferase activity was

compared to transcript levels to normalize for both transfection efficiency and mRNA

stability. The Photinus luciferase activity to mRNA ratio obtained from the β-globin

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Figure 5.4 Four leaders contain IRESes that are more active in the Aurora A over- expressing cell lines Reporter constructs containing the β-globin or various Aurora A 5’ leaders or the EMCV IRES were in vitro transcribed then capped with an ApppG cap analog and poly (A) tailed. The RNA constructs were transfected into each cell line as previously describe (see Figure 5.2). The Photinus luciferase activity to mRNA ratio obtained from the β-globin construct in HMEC cells was set to one and was used to normalize the ratios obtained from the β-globin construct and the other constructs in all cell lines. Any ratio greater than one indicated IRES activity. The results from the β- globin construct shows similar background levels between the four cell lines. The EMCV IRES is active in each cell line and 2 times more active in the MCF12A cells compared to the other 3 lines. Diagrams of the Aurora A, UC, tV2, UB, tV3 and tV5 5’ leaders are shown. They all demonstrate IRES activity. Yet the Aurora A, UB, tV3 and tV5 5’ leaders (blue boxes) having higher IRES activity in the high Aurora A expressing cells (MCF12A and MCF10A). These results indicate the presence of more than one Aurora A IRES element . In addition, the results suggest these IRES elements are differentially regulated. n=3 +SD

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construct in HMEC cells was set to one and was used to normalize the ratios obtained

from this construct and the other constructs in each cell lines (Figure 5.4). Any ratio

greater than one would indicate IRES activity. Ratios derived from the β-globin negative

control were all close to one in the 4 cell lines indicating background levels between the

lines were similar. Ratios from the EMCV positive control were 4 fold higher in HMECs, and 5 fold higher in MCF-7 and MCF10A cells indicating IRES activity in each line.

Activity from EMCV in MCF12A cells increased 11 fold compared to the negative control. The Aurora A construct was 2 fold higher than the control in low expressing

HMEC and MCF-7 cells. However the ratio from this construct increased in the high expressing MCF12As and MCF10As to7.5 and 7 fold respectively. There was IRES activity in all lines from the following leaders: UC, tV2, UB, tV3 and tV5. Therefore six of the nine leaders could be initiated cap-independenty. On the other hand, no IRES activity was obtained by UA, tV4 or, tV6. Interestingly, the ratio of Photinus luciferase activity to mRNA levels was increased in the Aurora A over-expressing lines (MCF12A and MCF10As) for Aurora A (exon Ib,II), UB (exon IIa only), tV3 (exon II only) and tV5

(exon II only) leaders compared to the low expressing lines (HMECs and MCF-7)

(Figure 5.4 blue boxes). These results indicate potential IRES activity from these leaders is contributing to enhanced Aurora A protein expression in MCF12a and MCF10A cells.

Additionally, the results suggest that leaders which contain exon II or exon IIa exhibit enhanced IRES activity in Aurora A over-expressing cell lines. By deduction, it appears that exon II inhibits IRES activity of exon Ib in low expressing cells but exon IIa does not

(compare Aurora A and UC leaders). Finally, as demonstrated by the UA leader, exon II

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and exon IIa IRES elements in the same variant do not exhibit IRES activity in any cell

line.

Exon II and exon IIa transcripts are associated with high molecular weight

polysomes in MCF12A cells

There are many Aurora A 5’ leaders present in the cell lines, yet the leaders

exhibit different IRES activity, suggesting they are differentially translated. To confirm

that the reporter constructs containing the different 5’ leaders were differently translated,

I measured steady state levels of Aurora A transcripts containing exon II or exon IIa in

the high expressing MCF12A cells and the low expressing MCF-7 cells. cDNA libraries

were constructed from total RNA isolated from the individual cell lines. Exon II and exon

IIa transcript levels were measured by qRT-PCR. Levels of both exon II and exon IIa

containing transcripts were similar between these two lines (Figure 5.5 top). Taken together with results from the reporter assays it appears the exon II and exon IIa transcripts are being translated at a greater rate in MCF12A cells than in MCF-7 cells.

Association with HMW fractions suggests increased translation initiation and/or

reinitiation as the result of more efficient loading of the ribosomes onto the mRNA

(Thomas and Johannes 2007). If IRES activity of transcripts containing either exon II or

exon IIa contributes to increased Aurora A protein levels there should be a greater

association of these transcripts with the high molecular weight (HMW) polysomes in the

high Aurora A protein expressing MCF12A cells versus the low Aurora A protein

expressing MCF-7 cells. To test this idea, polysome gradient analysis was performed (for

details see Figure 4.4). mRNA levels were quantified in nonpolysomal fractions 1 and 2,

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Figure 5.5 Exon II and exon IIa transcripts are associated more with the HMW polysome in MCF12A cells compared to MCF-7 cells High expressing MCF12A cells and low expressing MCF-7 cells were treated with cycloheximide, collected and prepared for fractionation via a sucrose gradient (see Chapter II for details). Total RNA from the nonpolysomal fractions (containing 40S, 60S, and 80S peaks, fractions 1-2), low molecular weight polysome fractions (disome and trisome, fractions 3-4)), and high molecular weight polysome fractions (> trisome, fraction 5-6) was isolated. Quantitation of Aurora A mRNA levels associated with the different gradient fractions was measured using qRT-PCR after isolation of total RNA from each fraction. n=3 +SD

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low molecular weight (LMW) polysome fractions 3 and 4, and high molecular weight

(HMW) polysome fractions 5 and 6. They were normalized to mRNA levels from

fraction 1 which was set to one. Levels of exon IIa transcripts in MCF12A cells increased

from the top of the gradient (nonpolysomal) to the bottom of the gradient (HMW

polysome). In contrast, exon IIa transcripts peaked in the LMW polysome fractions in

MCF-7 cells (Figure 5.5 bottom). Exon II transcripts also peaked in the LMW polysome

fraction in MCF-7 cells. In MCF12A cells there was a large amount of exon II transcripts

associated with the disome (fraction 3) and a second peak in the HMW polysome

fractions (Figure 5.5 bottom). These results indicate translational upregulation of both exon II and exon IIa Aurora A transcripts in the high expressing MCF12A cells compared to the low expressing MCF-7 cells.

PKM2 is identified as a potenial ITAF for the Aurora A 5’ leader in HeLa cells

For eukaryotic IRESes, the rate-limiting step is proposed to be the expression

level of non-canonical proteins termed IRES trans-acting factors (ITAFs) (reviewed in

(Hellen and Sarnow 2001)). Therefore RNA-binding proteins that regulate the Aurora A

IRESes would be the best candidates as biomarkers for enhanced Aurora A IRES activity.

With the help of a fellow Krushel labmate, Kris Veo, I attempted an RNA–affinity

binding assay (Figure 5.6 top). Briefly, RNA containing the Aurora A 5’ leader along

with the first 85 nt of the Photinus ORF, to help with proper folding of the leader, was in

vitro transcribed and a poly (A) tailed. The transcript was mixed with oligo dT beads and

then transferred onto a column. HeLa S10 lysates were run over the column allowing for

interaction between RNA-binding proteins and the leader. After the column was washed,

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Figure 5.6 PKM2 is a potential ITAF for the Aurora A 5’ leader IRES (Top) Schematic representation of the RNA binding assay used to identify an interaction between the Aurora A 5’ leader and PKM2. (Bottom) HeLa cells were transfected with 5 different PKM2 shRNA plasmids and incubated for 48 hr. Cells were then transfected with an ApppG capped monocistronic RNA containing the Aurora A 5’ leader. The Photunius activity to mRNA ratio decreased from 30-60% in knockdown cells compared to a control shRNA.

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the RNA-binding proteins were eluted off the column and sent out for mass

spectrometery analysis. Results were compared to those obtained for the

App and Tau IRESes, and the Bace 1 5’ leader to identify proteins that were uniquely

binding the Aurora A 5’ leader. A couple of candidate proteins were identified and tested

but to date only one, pyruvate kinase M2 (PKM2), has not been ruled out.

To determine if PKM2 regulated IRES activity from the Aurora A 5’ leader,

PKM2 expression was knocked down with a series of five different shRNAs (Figure 5.6

bottom). HeLa cells were transfected with shRNA plasmids and incubated for 48 hr prior

to RNA transfection. There was a 30-60% decrease in the Photinus activity:mRNA ratio of an ApppG capped moncistronic RNA contruct containing the original Aurora A 5’ leader compared to a control plasmid. Although the results are preliminary they are encouraging and warrant further investigation of PKM2 as a potential ITAF for the

Aurora A 5’ leader. Future experiments to validate these findings are detailed in the following discussion section.

The ERK signaling pathway may regulate IRES-dependent translation of the

Aurora A 5’ leader in HeLa cells

Regulation of cap-dependent translation by the mTOR pathway has been well studied. In contrast, pathways regulating IRES-dependent translation are poorly understood. To identify pathways that regulate the IRES activity of the original Aurora A

5 ‘leader, a human kinase/phosphatase siRNA screen was performed in HeLa cells

(Figure 5.7). This screen utilizes siRNA to knockdown 622 kinases and 247 phosphatases

in triplicate. HeLa cells were transfected with siRNA and incubated for 48 hours. An in

vitro transcribed m7G capped and poly (A) tailed dicistronic RNA construct coding for

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Figure 5.7 siRNA human kinase/phosphatase library screen A total of 622 kinases and 267 phophatases were evaluated in triplicate as potential regulators of IRES activity of the Aurora A 5’ leader. Cells were transfected with siRNA and incubated for 48 hours. The cells were then transfected with a dicistronic RNA contruct with a m7G cap and poly (A) tail containing the Aurora A 5’ leader in the intercistronic region. Four hours later cells were harvested and assayed for Photinus and Renilla activity.

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Renilla and Photinus luciferase in the first and second cistrons, respectively (Stoneley,

Paulin et al. 1998), and containing the original Aurora A 5’ leader in the intercistronic

region were transfected into the HeLa cells. Cells were harvested four housr later and luciferase activity was determined by a dual luciferase assay (Figure 5.7).

To mine the data from this screen, I identified kinase knockdowns that led to a decrease of the Photinus:Renilla ratio compared to controls (refer to Appendix C for complete results from the siRNA library screen). Numerous hits in the MAPK pathways immediately stood out including MEK1, MEK2, ERK1 and ERK2. Results from the NIH

David search program identified more kinases in the ERK signaling pathway (p < 1.1E-

18) than any other pathway were linked to decreased P:R ratios compared to control. The

ERK pathway was interesting since enhanced activity of the ERK pathway has been suggested to contribute to immortalization (Boucher, Jean et al. 2004).

MEK inhibitors decrease Aurora A protein expression in HeLa cells

To determine if the ERK pathway regulated Aurora A protein expression, the pathway was downregulated by two MEK inhibitors in HeLa cells. With the help of another Krushel labmate, Shihuang (Sam) Su, Hela cells were treated with MEK inhibitors (U0126-70nM and PD9805-7µM) for four hours. Cells were collected and

Aurora A protein and mRNA levels were measured as previously described (for details see Figure 4.1). In the presence of MEK inhibitors Aurora A protein levels decreased by approximately 70% (Figure 5.8). Aurora A mRNA levels remained unchanged (PB9805) or slightly elevated (U0126), therefore the ratio between Aurora A protein and mRNA levels decreased by 75-80% (Figure 5.8). These results suggest MEK inhibition in HeLa cells downregulates translation initiation of the Aurora A mRNA. On the other

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A Aurora A Gapdh

Figure 5.8 MEK inhibitors in HeLa cells Hela cells were treated with MEK inhibitors (U0126 - 70nM and PD9805 - 7µM ) for four hours. (A) Cells were collected and Aurora A protein and (B) mRNA levels were measured as previously described. (C) The Aurora A protein to mRNA ratios were determined as previously described. Aurora A protein levels decreased by approximately 70% while mRNA levels remained unchanged or slightly elevated. These results suggest that the ERK pathway regulates Aurora A protein expression. n=3 + SD

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hand, the decrease in Aurora A protein to mRNA ratio could be the result of decreased

protein stability. However, the results are consistent with the hypothesis that the ERK

pathway regulates Aurora A protein expression in HeLa cells.

EGF induces increased Aurora A protein expression

To determine if upregulated ERK signaling would affect Aurora A protein and

mRNA expression, epithelial growth factor (EGF) was used to induce the ERK pathway

in MCF12A cells. MCF12A cells already express high levels of Aurora A kinase and

demonstrate high IRES activity from the six Aurora A 5’ leader variants that initiate

translation internally (see Figures 4.1 and 5.4). MCF12A cells were serum starved for 16

hours prior to the addition of 10nM of EGF. Four hours after EGF induction the cells

were collected. Aurora A protein and mRNA levels were measured as previously

described (for details see Figure 4.1). Aurora A protein expression increased 1.5 fold

(Figure 5.9). In contrast mRNA expression decreased by 45%, therefore the Aurora A

protein to mRNA ratio increased over 3 fold (Figure 5.9). These results indicate a

possible feedback mechanism to increase Aurora A protein synthesis in response to

decreased Aurora A mRNA levels. Fellow Krushel labmate Juan Chen detected phosphorylation of ERK1/2 by western blotting along with Aurora A, Gapdh (loading control) and total ERK1/2 protein levels (Figure 5.9). An increase in ERK signaling and

Aurora A protein expression was detected after 30 minutes of EGF induction (Figure

5.9). Phosphorylation of ERK started to decrease within one hour of EGF induction but

Aurora A protein levels remained elevated after 4 fours (Figure 5.9). The quick increase in Aurora A protein levels in response to EGF induction supports the idea that activation of the ERK pathway upregulates translation initiation of the Aurora A mRNA.

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EGF Aurora A Gapdh Aurora A Gapdh p-ERK ERK

Figure 5.9 EGF induction increases Aurora A protein expression and decreases Aurora A mRNA levels in MCF12A cells MCF12A cells were serum starved for 16 hours, at which time 10 nM of EGF was added back to the media. Cells were harvested four hour later and Aurora A protein and mRNA levels were detected (for details see Figure 4.1). Aurora A protein levels increased even though a decrease of mRNA levels was detected. The experiment was repeated and cells were collected at various timpoints (indicated above). Protein levels were measured by western blot analysis. Both activation of ERK signaling as demonstrated by increase phosphorylation and Aurora A protein expression were elevated within 30 minutes of EGF induction. n=3 + SD

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To identify changes in the phosphorylation states of additional kinases and their

substrates in response to EGF induction in MCF12A cells a phospho-proteome array was performed. One interesting finding was the differential phosphorylation of the two AKT residues that are required for full AKT activation (Vincent, Elder et al. 2011).

Phosphorylation of AKT S473 increased in response to EGF induction. Conversely,

phosphorylation of AKT T308 decreased (Figure 5.9). Differential phosphorylation of

AKT substrates was also detected. For example no change in phosphorylation of p27

T127 was detected yet phosphorylation of GSK α/β S21/S29 increased (Figure 5.10A).

Additionally, phosphorylation of mTOR increased 3 fold in response to EGF induction.

Activation of both mTORC1 and mTORC2 complexes were also enhanced as shown by

increased phosphorylation of their individual substrates; p70S6 kinase T229/T421/S424

and AKT S473 respectively (Figure 5.10B). Additionally, a 4 fold increase of translation initiation of a cap-dependent m7G capped poly (A) tailed RNA reporter in +EGF

conditions compared to –EGF conditions indicated mTORC1 activity was upregulated

(Figure 5.10C).

Proteome array of the four breast lines

To determine if this phosphorylation pattern was similar in the other breast lines

(HMEC, MCF10A, and MCF-7) I examined the phospho-proteome array with lysates from these all four lines under normal growth conditions (Figure 5.11). Phosphorylation of ERK 2 was similar between the four lines but ERK 1 phosphorylation was only detected in MCF-7 cells. mTOR phosphorylation was high in the high Aurora A protein expressing MCF10A and MCF12A cells compared to the low Aurora A expressing

HMEC and MCF-7 cells. The mTOR pathway may be involved in upregulating activity

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Figure 5.10 EGF induction in MCF12A cells affect AKT and mTOR signaling Blots of a human kinase proteome array from MCF12A cells + 10 nM EGFare shown. (A)The red line underlines the AKT S473 phosphorylation dots (left) and AKT T308 phosphorylation dots (right). (B) The red line underlines mTOR. Each dot was quantitated by ImageQuant software and normalized to the nearest positive control (for key see Appendix D). Results for AKT S473 & T308, p27 T157, GSK3α/β S21/S9, mTOR, p70S6K T421/S424 & T229 were graphed. (C) Cap-dependent translation was increased by 4 fold after EGF induction.

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Figure 5.11 Phosphorylation states of ERK, AKT and mTOR residues under normal growth conditions Blots of a human kinase proteome array from HMEC, MCF-7, MCF12A and MCF10A cells under normal growth conditions are shown. The red line underlines the AKT S473 phosphorylation dots (left) and AKT T308 phosphorylation dots (right). Each dot was quantitated by ImageQuant software and normalized to the nearest positive control (for key see Appendix D). Results for AKT S473, T308 and ERK1/ERK2 were graphed. MCF12A and MCF10A cells demonstrate an increased level of AKT p-S473 and mTOR (see AppendixD) compared to HMECs and MCF-7 cells. Conversely, AKT p-308 is lower in the former lines compared to the latter. No difference was detected in phosphrylation of ERK2. However phosphorylation of ERK1 was detected only MCF-7 cells.

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from the exon II and exon IIa IRESes. The most interesting finding was the

phosphorylation states of AKT S473/T308. Phosphorylation of S473 was 3 times

higher in MCF10A and MCF12A cells compared to HMECs. It was not detected in

MCF-7 cells. In contrast, phosphorylation of T308 was higher in HMECs and MCF-7

cells compared to MCF10A and MCF12A cells (Figure 5.11). Therefore the ratio

between p-S473/p-T308 in the high Aurora A protein expressing /high exon II and exon

IIa IRES activity cells correlates with what was found in the +EGF conditions in

MCF12A cells. The results indicate a specific AKT target (or AKT directly) may regulate

Aurora A IRES activity in response to the changes in the phosphorylated states of these

AKT residues.

EGF induces increased activity of the exon II IRES in MCF12A cells

To determine if IRES activity contributed to enhanced Aurora A protein

expression in response to EGF induction in MCF12A cells, cap-independent translation

initiation of the Aurora A 5’ leader was measured by the ApppG assay. In addition, IRES

activity from Aurora A exons II or IIa independently or within the same construct (exon

II/IIa) was measured. MCF12A cells +/- 10nM EGF were transfected with the various

ApppG capped, poly (A) tailed, monocistronic Photinus RNA reporter constructs. Four

hours later, cells were collect and Photinus activity and transcript levels were measured

as previously described (see Figure 5.2) The Photinus activity: transcript ratio of each

construct in –EGF conditions was normalized to one. The ratio obtained from +EGF

conditions indicate the change in IRES-dependent translation initiation of the specific

transcript. There is a 3.5 fold increase of IRES activity from the original exon II containing Aurora A leader after EGF induction (Figure 5.12 top) Similarly IRES activity

185 of exon II by itself increased 3 fold after EGF induction. IRES activity of exon IIa and exon II/IIa was unchanged.

I repeated this experiment in MCF12A cells with various Aurora A 5’ leaders along with the EMCV IRES as a positive control. This time the Photinus activity: transcript ratio obtained from the original Aurora A 5’ leader in –EGF conditions was normalized to one and compared to all other ratios (Figure 5.12 bottom). IRES activity of exon II containing 5’ leaders was enhanced in the presence of EGF. Again there was a 3 fold increase of IRES activity from the original Aurora A leader in +EGF conditions.

Similarly, IRES activity from the tV3 (exon II) leader increased 3 fold in +EGF conditions. IRES activity from the tV5 (exon II) leader increased 1.5 fold in the presence of EGF. Activity of the other leaders (UA-exon II/IIa leader and UB- exon IIa leader) and the EMCV IRES was relatively unchanged. Taken together, the results suggest IRES activity from an exon II containing leader which is not in combination with exon IIa, is upregulated by EGF induction. They also support the hypothesis that the Aurora A IRES elements are differentially regulated.

Exon II containing Aurora A transcripts are associated with HMW polysomes in response to EGF induction in MCF12A cells

To determine if translation of exon II containing Aurora A messages is upregulated by EGF induction in high Aurora A expressing cells, polysome gradient analysis from +/- EGF MCF12A cells were compared to +/- EGF MCF-7 cells (Figure

5.13 top). After 16 hours of serum starvation, Aurora A protein expression levels were unaffected by EGF induction in MCF-7 cells. These cells are known to have low levels of

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Figure 5.12 EGF induces activity of the exon II IRES in MCF12A cells Four hours after 10 nM of EGF was introduced to serum starved MCF12A cell, IRES activity of ApppG capped and poly (A) tailed monocistronic RNA constructs encoding Photinus luciferase and containing Aurora A exons and 5’ leaders the EMCV IRES exons were measured (see Figure 5.2 for details of the experiments). For the top graph IRES activity of each reporter construct in –EGF conditions were set to one and were compared to activity from the same reporter in +EGF. For the bottom graph all ratio were normalized to the ratio obtained by the original Aurora A leader in –EGF conditions which was set to one. IRES activity of exon II containing 5’ leaders was enhanced in the presence of EGF while activity of the other leaders and the EMCV IRES was relatively unchanged. n=3 + SD

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Figure 5.13 Exon II transcript association with the HMW polysome in MCF12A cells increases in response to EGF induction. Cells were serum starved for 16 hours and then exposed to 10nM of EGF. After four hours cells were harvested, lysate and fractionated over a 20-60% sucrose gradient. Total RNA from the nonpolysomal fractions (containing 40S, 60S, and 80S peaks, fractions 1-2), low molecular weight polysome fractions (disome and trisome, fractions 3-4)), and high molecular weight polysome fractions (> trisome, fraction 5-6) was isolated. Quantitation of all Aurora A, exon II containing, and exon IIa containing mRNA levels associated with the different gradient fractions was measured using qRT-PCR. Targeting the ORF to measure the total Aurora A transcript levels demonstrated a large increase in association with the HMW polysome in response to EGF in MCF12A cells. A similar response was detected with exon II transcripts but exon IIa transcripts were minimally affected. In contrast only small changes were detected in MCF-7 cells after EGF induction. However, association with the polysome was slightly decreased with exon II and exon IIa transcripts after EGF induction. Western blots reveal Aurora A levels are unaffected in MCF-7 cells after EGF induction as well.

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EGFR. However, EGF induced ERK phosphorylation in MCF-7 cells. The results

indicate the low levels of EGFR in MCF-7 cells are sufficient to induce the ERK pathway or a different receptor is involved.

Polysome analysis was performed by fractionating lysates on a sucrose gradient

were collected four hours after EGF induction. Aurora A mRNA levels were quantified in

nonpolysomal, low molecular weight (LMW) polysome and high molecular weight

(HMW) polysome fractions. Association with HMW fractions suggests increased

translation initiation and/or reinitiation as the result of more efficient loading of the

ribosomes onto the mRNA (Thomas and Johannes 2007). Association of total Aurora A

mRNA with HMW polysome fractions was greatly increased in MCF12A cells after EGF

induction (Figure 5.13 bottom left). This increased association with the HMW fractions

in response to EGF was also seen with exon II containing Aurora A mRNA in

MCF12Acells (figure 5.13 bottom middle). Distribution of exon IIa containing transcripts

between the fractions was minimally increased after EGF induction compared to what

was seen with total Aurora A mRNA or exon II containing Aurora A mRNA in MCF12A

cells (Figure 5.13 bottom). In contrast, total Aurora A mRNA, exon II and exon IIa

containing Aurora A transcripts were unaffected by EGF induction in MCF-7 cells. These results support the hypothesis that EGF induces increased translation of exon II containing Aurora A transcripts in over-expressing cell lines, whereas this signaling mechanism is absent in “normal” or low Aurora A expressing cells.

In summary, my results indicate a relatively novel mechanism where protein synthesis is regulated by the cell selectively choosing a subset of mRNA (demonstrated by the differing Aurora A 5’ leaders) but containing the same ORF. These results support

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the hypothesis that EGF induction signals increased translation of exon II containing

Aurora A transcripts in MCF12A cells. However, EGF induction does not affect

translation of Aurora A mRNA in low Aurora A expressing cell MCF-7 cells. This result

suggests additional factors are differentially expressed and/or activated between

MCF12A cells and MCF-7 cells. I propose these factors are Aurora A exon II regulating

ITAFs that are functionally upregulated in response to EGF induction of ERK, AKT,

and/or mTOR signaling that leads to enhanced Aurora A exon II IRES activity and

protein expression, contributing to cellular immortalization and possibly transformation.

Discussion

The 5’ UTR of the Aurora A gene consists of five exons which I have demonstrated can be alternatively spliced forming nine different variants, all of which

encode the same protein. Six of these variants can initiate translation cap-independently.

Three of the five exons that are alternatively spliced have potential IRES activity.

Activation of these IRES elements is dependent on the combination of the elements in the

5’ leader of the Aurora A mRNA. The exon Ib IRES is active in high or low Aurora A

protein expressing cell lines if not in combination with exon II. Exon II IRES activity is

upregulated in high Aurora A expressing cell lines versus low expressing lines. The same

is true for exon IIa IRES activity. However, a leader containing both exon II and exon IIa

cannot initiate translation cap-independently. These results suggest the three IRES

elements are differentially regulated.

Activation of the ERK, AKT and/or mTOR signaling in response to EGF

induction leads to increased Aurora A protein expression in MCF12A cells. Aurora A

mRNA levels decrease under these conditions in MCF12A cells supporting the idea that

190 the increase in Aurora A protein expression is due to increased protein synthesis. Results from the polysome gradient assays showed a large increase in the association of exon II containing transcripts with HMW polysomes after EGF induction in MCF12A cells.

Therefore, I propose enhanced expression of Aurora A protein is the result of increased

IRES activity of exon II containing Aurora A transcripts in MCF12A cells.

Why are there multiple 5’ leaders all of which contain the same ORF?

Nine different 5’ leaders derived from alternative splicing of five exons in the 5’

UTR of the Aurora A gene were detected in the cell lines used in this study. Total Aurora

A transcripts were similar between these lines as determined by targeting the Aurora A

ORF using qRT-PCR. Targeting the individual transcripts is complicated by the repeated use of exon-exon junctions between the varying leaders. For this reason I am targeting the individual exons. To date, I’ve found similar levels of exon II and exon IIa containing transcripts between the low Aurora A protein expressing MCF-7 cells and the high

Aurora A expressing MCF12A cells. Additionally, when identifying the different variants the amount of PCR products which turned out to be the exon II containing tV3 and tV5 suggested these leaders are the most abundant. However, qRT-PCR is still needed to determine if this is the case since using the same primer set to find the different variants would result in a faster accumulation of smaller products. Both tV3 and tV5 are approximately 150 bp compared to the 366 bp of the Aurora A 5’ leader. The result of the polysome gradient analysis supports the idea that exon II leaders are most abundant since the association with the polysome was very similar between exon II transcripts and total

Aurora a transcripts. Additionally, these results suggest the exon II IRES may have an important role in regulating Aurora A expression.

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Multiple mechanisms may contribute to over-expression of Aurora A protein

Prior to this study mechanisms contributing to Aurora A over-expression have focused on DNA-mediated mechanisms. Enhanced expression of Aurora A protein in tumors is reportedly due to a concomitant increase in Aurora A mRNA owing to gene amplification and/or increased transcription (Tanner, Tirkkonen et al. 1994; Tanner,

Tirkkonen et al. 1995; Bischoff, Anderson et al. 1998; Zhou, Kuang et al. 1998; Tanner,

Grenman et al. 2000). However, not all of these studies examined the effect these mechanisms had on actual protein expression. RNA levels do not always represent protein expression. In this study I have found ten cell lines with the same steady levels of

Aurora mRNA expression and similarities in protein stability yet vary in steady state

Aurora A protein levels (see Chapter IV). Additionally, I have demonstrated that EGF induction in MCF12A cells resulted in enhanced expression of the protein but mRNA levels decrease. Aurora A exon II IRES activity was enhanced as well. Therefore an increase in cap-independent protein synthesis of Aurora A exon II containing transcripts can contribute to unregulated Aurora A protein expression despite decreased mRNA expression.

A recent study in MCF-7 cells demonstrated increased transcription in response to estrogen resulted in enhanced Aurora A protein expression (Jiang, Katayama et al. 2010).

The cells in my studies are early passage cells (<20). I have seen enhanced expression of

Aurora A protein levels in late passage MCF-7 cells compared to early passage MCF-7 cells. Aurora A mRNA levels also increase in these late passage cells. Therefore, the protein to mRNA ratio remained the same between early and late passage MCF-7 cells.

Additionally there is no difference in Aurora A IRES activity. These findings

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demonstrate that different mechanisms are contributing to Aurora A expression in cancer

cell lines. Differentiating between these mechanisms would be beneficial when

determining the best approach to treat Aurora A over-expressing cancers.

For eukaryotic IRESes, the rate-limiting step is proposed to be the expression

level of non-canonical proteins termed IRES-transacting factors (ITAFs) (reviewed in

(Hellen and Sarnow 2001)). Therefore RNA-binding proteins that regulate the Aurora A

IRESes would be the best candidates as biomarkers for enhanced Aurora A IRES activity.

PKM2 was identified by an RNA binding assay to interact with the Aurora A 5’ leader.

Additionally, Aurora A IRES activity was inhibited when PKM2 was targeted by 5

different shRNA plasmids. Looking closer at the siRNA library I noticed two out of three

siRNA knockdowns of PKM2 resulted in a decrease in the P:R ratio by 34% and 42% in

HeLa cells (see Appendix C).

The PKM2 isoform is a rate-limiting glycolytic enzyme involved in the Warburg effect (Ferguson and Rathmell 2008). It is exclusively expressed in embryonic, proliferating, and tumor cells, and plays an essential role in tumor metabolism and growth (Sun, Chen et al. 2011; Ferguson and Rathmell 2008). Although best known for its role in the Warburg effect PKM2 expression is upregulated under normoxic conditions by mTOR. Additionally, disruption of PKM2 inhibited oncogenic mTOR-mediated tumorigenesis (Sun, Chen et al. 2011).

Many additional experiments will need to done before PKM2 can be considered a legitimate ITAF of the IRES elements present in the Aurora A leader. First knockdowns need to be verified by western blotting. Testing IRES activity from the exons and additional Aurora A leaders will be required to pin down which IRES PKM2 may be

193 regulating since the Aurora A 5’ leader contains both exons Ib and exon II. Additionally, the effect on Aurora A protein and mRNA levels will need to be determined. And finally, confirmation of PKM2 binding the Aurora A 5’ leader should be determined by performing a RNP immunoprecipitation assay (RIP) or filter binding assays. If PKM2 is an ITAF for the Aurora A exon II IRES a screen with small molecule inhibitors could be attempted.

Signaling pathways and Aurora A IRES activity

Signaling pathways regulating specific cellular IRESes have been demonstrated.

For instance, the cyclin D1 and the c-myc IRESes are negatively regulated by AKT activity. In addition, IRES activity from these two IRESes is enhanced following exposure to rapamycin in a p38 MAPK and RAF/MEK/ERK signaling-dependent manner

(Shi, Sharma et al. 2005). In this study I have found inhibition of MEK in HeLa cells results in decreased Aurora A protein expression in the absence of decreased Aurora A mRNA levels. I have also demonstrated EGF induction in MCF12A cells results in increased Aurora A protein expression while Aurora A mRNA levels decrease. EGF induction in MCF12A cells also increases IRES activity of the exon II IRES. This finding was support by the enhanced association of exon II containing Aurora A transcripts with the HMW polysomes after EGF induction. In contrast, EGF induction did not affect

Aurora A protein expression in MCF-7 cells and exon II Aurora A transcripts in this cell line did not associate with the HMW polysome. The ERK pathway was identified by a siRNA kinase/phosphatase library screen to affect Aurora A IRES activity. Interestingly

EGF induction did result in increased phosphorylation of ERK in both cell lines. This

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finding suggests a differential response occurring downstream of ERK between these two

lines or ERK signaling is not involved in Aurora A IRES activity after EGF induction.

Differential phosphorylation of AKT may contribute to Aurora A IRES activity.

This serine/threonine kinase is a central player in cell signaling downstream of growth

factors, cytokines, and other cellular stimuli. AKT activation requires the

phosphorylation of T308 in the activation loop by the phosphoinositide-dependent kinase

1 (PDK1) and S473 within the carboxyl-terminal hydrophobic motif by PDK2 or mTORC2. Typically measuring phosphorylation of S473 alone has been used to determine AKT activity (Vincent, Elder et al. 2011). However there is mutational evidence that shows that phosphorylation specific AKT substrates vary in response to differential regulation of both S473 and T308 (Yung, Charnock-Jones et al. 2011;

Jacinto, Facchinetti et al. 2006). Therefore determining phosphorylation states of both residues would be more informative in terms of downstream affects of AKT activity.

There is no detectable phosphorylation of AKT S473 found in MCF-7 cells but AKT

T308 is phosphorylated. Conversely, S473 is highly phosphorylated in MCF12A cells but

phosphorylation of T308 is lower than seen in MFC-7 cells (see Figure 5.11). After 16 hours of serum starved conditions the phosphorylation states of S473 and T308 are similar to each other in MCF12A cells. Four hours after EGF induction the phosphorylation states of these residues resemble what is seen in MCF12A and MCF10A cells under normal growth conditions (see Figure 5.11). This high p-S473 to low p-T308 ratio correlates with increased exon II IRES activity and enhanced Aurora A protein expression. Identifying phosphorylation of specific AKT substrates under these different

195 conditions could lead to the identification of a biomarker for exon II IRES activity contributing to over-expression of Aurora A protein.

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CHAPTER VI

CONCLUSIONS AND FUTURE DIRECTIONS

In this study, I have demonstrated how IRES-dependent translation initiation could contribute to two otherwise unrelated diseases: Fragile X Syndrome (FXS) and cancer. First, I have identified specific regions in the 5’ leader of the FXS-associated

FMR1 mRNA, including the disease defining CGG trinucleotide repeats that regulate its

IRES activity. Additionally, I have shown that FMR1 IRES activity responds to stimuli known to affect both expression and activation of the FMRP protein. Secondly, I demonstrated that IRES-dependent translation is a contributing mechanism to Aurora A protein over-expression in a subset of immortalized cell lines. Three out of the five exons that are alternatively spliced to create the various 5’ leaders of Aurora A messages can initiate translation cap-independently. Finally, I demonstrated that Aurora A IRESes are differentially regulated and that activity from one (exon II) can be upregulated by signaling pathways known to contribute to cancer development, specifically cellular immortalization.

Why Study Translation Initiation of Cellular Messages?

Until recently, gene expression was synonymous with mRNA expression.

Mechanisms that regulated transcription have been widely studied in our attempt to better understand disease including trinucleotide repeat disorders and cancer. These mechanisms include gene accessibility controlled by chromatin remodeling (Bell and

Dutta 2002), transcription factor activation controlled by intercelluar and intracellular signaling (Benz 1998), and mRNA stability controlled by numerous mechanisms during

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pre-mRNA processing as well as cytoplasmic degradation (Balatsos, Maragozidis et al.

2012; Jin, Alisch et al. 2004).

Studying mechanisms that contribute to misregulated mRNA expression in

disease makes sense. Without mRNA there is nothing to translate. Indeed, inhibiting transcription of oncogenes or upregulating transcription of tumor suppressor genes can inhibit tumor progression (Bellodi, Kopmar et al. 2010; Kim, Forman et al. 2000; Chen,

Chang et al. 2002; Moynahan 2002; De Benedetti and Graff 2004; Wang, Zhou et al.

2006; Ishimaru, Ramalingam et al. 2009). In FXS, the CGG repeat expansion inhibits

transcription which results in the absence of FMRP expression. However, there are

studies showing mRNA levels do not always correlate with protein expression in both

cancers (Lai, Tseng et al. 2010) and FXS-associated disorders (Tassone, Hagerman et al.

2000).

A recent study of transcriptomes and proteomes in eukaryotic cells demonstrated

that protein levels are best explained by translation rates versus transcription rates

(Schwanhausser, Busse et al. 2011). Indeed, there are certain cellular events that depend

on de novo protein synthesis but are independent of de novo transcription. For example

neural activity-dependent translation is seen in neurons. Signaling in neurons via

NMDAR, a glutamate receptor, regulates Wnt5a protein expression independent of

transcription (Li, Li et al.2010). As discussed in the introduction, specific mRNAs are dendritically localized in neurons. Through interaction with RNA-binding proteins these mRNAs are protected from degradation but not translated until the neuron receives the proper signal. Another study demonstrated that protein synthesis in response to cancer causing agents can occur without upregulated transcription. Ionizing radiation (IR)-

198 induced apoptosis in the human T cell line MOLT-4 cells requires de novo protein synthesis but not de novo RNA synthesis (Taylor, Buckwalter et al. 2002). Inhibition of protein synthesis but not transcription after IR results in the survival of cells with damaged DNA. Clearly, regulation of protein synthesis is not only important but required for such cellular events. There is a correlation between mRNA levels and protein levels, but the above examples demonstrate why mRNA levels are not always the best representatives of protein expression. I question how many of these types of occurrences have been missed in recent years with such a high emphasis placed on the results from high-throughput techniques without measuring the end product of genetically transferred information – the protein.

Why Study IRES-dependent Translation Initiation?

The main mechanism to initiate translation is cap-dependent translation initiation

(Merrick 2004). Indeed, every cellular mRNA has the 5’ m7G cap structure and therefore can be recognized by eIF4E to initiate this process. However, there are subsets of 5’ leaders that are characteristically inefficient at initiating translation by the cap-scanning mechanism. Many of the mRNAs with these long 5’ leaders that are often G/C rich

(suggesting a high likelihood of strong secondary structure) and may contain uORFs are translated during events when cap-dependent translation is compromised. Cap-dependent translation in neuronal dentrites is limited to the amount of rate-determining eukaryotic initiation factors, yet dendritically localized mRNA, including the FMR1 transcript, is efficiently translated in response to neuronal signals. Cap-dependent translation is also downregulated during the G2/M phase of the cell cycle (Tarn and Lai 2011) but there are many proteins, including Aurora A, that are exclusively expressed at this time (Cornelis,

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Bruynooghe et al. 2000; Pyronnet, Pradayrol et al. 2000; Cornelis, Tinton et al. 2005;

Tinton, Schepens et al. 2005). Not surprisingly, leaders of some dendritically localized

mRNA or those expressed during G2/M as well as various oncogenes and tumor

suppressor genes possess these cap-scanning impeding characteristics (see Table 1.1).

Therefore the existence of an additional mechanism that could be efficiently regulated

and initiate translation of leaders with these characteristics would be beneficial. I propose

that mechanism is IRES-dependent translation initiation.

The vast majority of dendritically localized mRNA or mRNA translated during

G2/M does not contain an IRES. Cap-dependent translation is always a potential

contributor to the initiation of any cellular mRNA. Additionally, one could argue the

presence of these cap-dependent inefficient leaders is because the cell does not require a

high amount of that specific protein. However, the high preponderance of dendritically

localized mRNAs containing IRESes suggests that IRES-dependent translation is an important protein synthesis mechanism in dendrites. Similarly, there are numerous cancer causing genes that have been shown to be regulated by an IRES, indicating the importance of this mechanism in cancer development. Based on the categories in which these mRNAs are commonly found (see Table 1.1), I hypothesize IRES-dependent translation initiation is an alternate mechanism to control synthesis of proteins whose expression is both temporally and spatially specific thereby requiring precise regulation greater than can be provided by a global mechanism. Additionally, I think studying the mechanism(s) of IRES-dependent translation initiation will lead to the identification of novel targets for anticancer drug development, will reveal how to regulate FMRP

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expression in FXS pre-mutation allele carriers and will lead to a new way of thinking

about translational control in eukaryotes.

But Do Cellular IRESes Even Exist?

IRES-dependent translation initiation has been under attack in terms of its

contribution to overall protein synthesis as well as its very existence in eukaryotic cells

(Kozak 2001; Kozak 2005). Evidence indicates that the majority of cellular protein is

synthesized in a cap-dependent manner. But the majority of proteins in the cell at any

given time are housekeeping genes. These genes are translated from mRNA with short

(50 nt) unstructured 5’ leaders which makes them suitable for efficient cap-dependent

translation because of minimal resistance for scanning by the pre-initiation complex

(Kozak and Shatkin 1978; Kozak 1986). On the other hand, transcripts with long, highly structured 5’ leaders are inefficiently translated via cap-dependent initiation. It has been argued that translation of these transcripts compared to transcripts with short unstructured leaders is affected to a greater extent when cap-dependent translation is inhibited (Kozak

2001; Kozak 2005). Therefore, minimal inhibition of cap-dependent translation initiation would not downregulate expression of the more efficiently translated housekeeping genes. The other genes are regulated based on how efficiently they can be translated in a cap-dependent manner. For example, sequestering eIF4E by the 4E-BPs will affect translation of cap-inefficient mRNAs more than housekeeping genes. However, translation from some of these cap-inefficient mRNAs have been shown to escape this type of regulation suggesting there is more than one mechanism regulating recruitment of the ribsome to eukaryotic mRNA.

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The debate about the existence of an alternate mechanism to initiate translation of eukaryotic messages is on. In addition to ribosomal scanning other “cap-dependent” mechanisms have been introduced to explain how long, structured leaders with upstream open reading frames (uORFs) can be efficiently translated (see Introduction). However every one of these mechanisms can be utilized with IRES-dependent initiation as well.

How the translation machinery is recruited to a leader does not determine which mechanism will be used to identify the initiator codon. Another argument is in regards to the “strength” of cellular IRESes.

Viruses need to initiate translation after hijacking the cells translational machinery

(Filbin and Kieft 2009). A subset of viruses maintains translation of the viral message after inhibiting global protein synthesis of the cell via IRES-dependent translation. These are some of the strongest IRESes, which would be expected since their function is to generate as much viral protein as possible. Critics of cellular IRESes often compared them to viral IRESes, stating cellular IRESes are weak and therefore inefficient in terms of initiating translation. However, some viral IRESes like the CrPV IRESes are also weak by comparison but without an attack on their existence. Cellular IRESes are often found on transcripts encoding proteins that are not highly expressed and expression needs to be tightly regulated (see Table 1.1). A strong IRES would not be functionally compatible with these requirements. The Aurora A protein is required for numerous events during

G2/M but if protein levels are not properly regulated the cells either die (repressed expression) or bypass the important G2/M checkpoint (enhanced expression) which could eventually result in tumorigenesis (Li, Zhu et al. 2003; Wang, Zhou et al. 2006; Fu, Bian et al. 2007; Wan, Long et al. 2008). Protein degradation and transcription of Aurora A are

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tightly regulated further demonstrating the importance of tight control of its gene

expression (Marumoto, Zhang et al. 2005; Fu, Bian et al. 2007; Kollareddy, Dzubak et al.

2008). Is it not logical that protein synthesis itself also be tightly regulated? Strong

activity from the Aurora A IRESes could actually be detrimental to the cell. So even

though mechanistically viral IRESes and cellular IRESes are similar, comparing activity

between them is unfair due to their differences in function.

Cellular IRESes differ from viral IRESes due to the presence of an m7G cap

structure. These transcripts may be able to utilize either cap or cap-independent

mechanisms. Both mechanisms are most likely not used simultaneously, particularly if

cap-dependent translation is followed by scanning. This mechanism would disrupt the

potential secondary structure and interactions with RNA-binding proteins of the IRES.

However if other mechanisms are used to identify the initiator codon, such as ribosomal

shunting, tethering or clustering it is a possibility that the 40S ribosomal subunit is recruited at the 5’ end of the leader and internally. Regardless, the ability of being able to initiate translation by either mechanism allows for continued expression of the encoded protein when cap-dependent regulation is inhibited. Additionally, an m7G capped transcript may be present in the cell but only translated when cap-dependent translation is repressed and IRES-dependent translation is upregulated.

Admittedly, methods use to identify IRESes contribute to the misconception that eukaryotic IRESes do not exist. Without an identifying consensus sequence or structure the only way to determine it a cellular leader has an IRES is by functional analysis. Early studies were plagued by lack of controls resulting in criticism that positive hits were nothing more than leaky scanning, reinitiation, cryptic promoter activity or cryptic

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splicing events (Kozak 2001; Kozak 2005). However as the field moved forward many stringent controls were developed. With sufficient controls in place, the 5’ leader of a cellular mRNA is said to contain an IRES if all other possibilities are ruled out and IRES activity is the only explanation left. Still, further investigation is required to determine if these IRESes are actually utilized to initiation translation of the mRNA.

What Were Once Vices Are Now Habits: The History of IRES Assays

One of the first and most commonly used experiments to determine if a leader can be translated cap-independently is the dicistronic DNA construct assay (Macejak and

Sarnow 1991; Stoneley, Paulin et al. 1998). A DNA plasmid encoding for a dicistronic message is transfected into cells and transcribed by an SV40 promoter. The β-globin 5’ leader regulates translation of the upstream cistron by cap-dependent initiation and serves an internal control for transfection efficiency. The sequence being tested for IRES activity is placed in the intercistronic region of the transcript. The upstream cistron is translated cap-dependently and serves an internal control for transfection efficiency. The downstream cistron will be translated only if an IRES is present in the intercistronic region. This assay is a good first step. Many cellular IRESes are initially discovered using dicistronic DNA. Unfortunately this assay results in a lot of false positives. Therefore, additional experiments are needed to determine if the detected expression of the second cistron resulted from activity of an IRES.

Some of the potential IRESes identified by the dicistronic DNA assay were determined to be nothing more than cryptic promoter activity, cryptic splicing, leaky scanning or reinitiation. In response, many methods were devised to determine if the potential IRES activity was real. First northerns with probes designed against the second

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cistron were used to look at messages transcribed by the DNA construct. A single dicistronic message is good but the presence of a second smaller message suggests cryptic promoter or cryptic splicing activity. The Renilla gene often used as the first cistron does contain a multitude of transcription factor binding sites that could contribute to such activity. Unfortunately northerns were shown not to be sensitive enough to identify small quantities of a cryptic message according to critics. Therefore, other alternatives to look for cryptic messages activity are utilized. RT-PCR is use to compare levels of PCR products generated from the first cistron to those generated from the second cistron. RNA protection assays are also used but this assay could miss aberrant

transcripts lacking the intercistronic region. Using siRNA targeting the upstream cistron

is another good assay. If translation of both cistrons is decreased by the same amount it

would indicate a single dicistronic construct was transcribed. Promoterless dicistronic

constructs are also used to eliminate cryptic promoter activity but I found these constructs

to be unreliable as I often detected translation of the upstream cistron.

A second approach to identify IRESes is to transfect cells with in vitro transcribed

dicistronic RNA constructs. This transcript would also be m7G capped and poly (A)

tailed. Indeed, the most efficient way to rule out cryptic promoter activity is by switching from DNA to in vitro transcribed dicistronic RNA constructs. However, even though switching to RNA removes interference of cryptic promoters and most aberrant splicing events it does not eliminate the possibility of ribosomal shunting after recruitment by the cap structure or readthrough of the upstream stop codon. To combat this issue an ApppG cap can be used to replace the m7GpppG cap thereby inhibiting translation of the upstream ORF. If an IRES is present in the intercistronic region translation of the second

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cistron would not depend on translation of the first. Of course by inhibiting translation of

the upstream cistron the benefit of an internal control for transfection efficiency is also

eliminated. Another solution is to place a hairpin just downstream of the stop codon of

the first cistron. This placement allows for translation of both cistrons but should reduce translation of the second cistron by shunting or leaky scanning. However, I found this construct had no effect on background translation of the second cistron.

Measuring IRES activity using dicistronic RNA reporter constructs instead of

DNA constructs usually results in decreased IRES activity. Eukaryotic IRES activity from in vitro transcribed RNA constructs is often weak compared to viral IRESes, particularly the EMCV IRES which is often used as a positive control. As I explained above many viral IRESes have robust activity due to the need to translate a large amount of protein. The EMCV IRES can internally initiate translation like a champ. Most cellular

IRESes that I have tested this way can initiate translation of a dicistronic transcript, DNA

or RNA, comparable to activity of the CrPV IRES.

Decreased IRES activity from an RNA construct compared to a DNA construct

can be explained by cryptic promoter activity. However when cryptic promoter activity is

not present, a reasonable explanation for this finding is the lack of a nuclear history. To

date there is no direct evidence that demonstrates activity of a cellular IRES requires a

nuclear experience. However, it has been suggested that nuclear modification of the

mRNA, such as methylation or pseudouriylation, may be required for full activity of a

cellular IRES (Thompson 2012). Another important nuclear event that could be missed

involves the association of the IRES with a regulating RNA binding-protein. Many of the

identify ITAFs would first come in contact with an IRES in the nucleus since they are

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involved in either pre-mRNA processing and/or nucleus to cytoplasm transport. In fact

only a few known ITAFs are located solely in the cytoplasm (Pacheco and Martinez-

Salas 2010).

The major limitation to using dicistronic constructs is that the majority of eukaryotic mRNA is monocistronic. Circularity of mRNA may promote translation at the cap versus the IRES in the middle of the transcript. Potential interactions between the

IRES and the 3’UTR could be compromised due to competition with the m7G cap of the upstream cistron. Structural integrity of cellular IRESes with relatively weak interactions could be compromised in a dicistronic construct. Therefore I would argue that testing the potential activity of a cellular IRES in a more natural context increases the physiological relevance of the results.

The assay I believe most rigorous for indentifying IRESes involves the transfection of a single in vitro transcribed ApppG capped and poly (A) tailed RNA reporter message. Comparing translation activity from the ApppG capped reporter to the level of reporter transcripts present in the cell allows for direct comparison of potential

IRES activity between any cell lines. With this assay both transfection efficiency along with mRNA stability can determined. However, this method still has one big caveat and that is lack of a nuclear experience. There both DNA and RNA monocistronic assays that can be used to look for potential IRESes. Classically, cotransfection of a second monocistronic reporter was used to control for transfection efficiency. Although the DNA experiments would involve a nuclear history I am apprehensive. A hairpin would be needed to inhibit cap-dependent translation of the message and this could potentially affect cis-elements at the 5’ end of the leader. Additionally background levels could be a

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concern like those seen with the dicistronic constructs. The effect of adding a hairpin

could be tested first using RNA transcripts. Compare expression from an ApppG capped

transcript with the hairpin to an ApppG capped transcript without it. If IRES activity

between these reporters is similar proceed with the DNA assay.

The 5’ Leader of the FMR1 mRNA Contains a Real IRES

Cap-dependent translation initiation has been observed in neuronal dendrites (Han

and Zhang 2002; Van Eden, Byrd et al. 2004) but it may be insufficient to ensure

efficient translation of dendritically localized mRNAs. eIF4E may be present in a lower

concentration in dendrites. Ribosomes may also be present in limiting amounts in

dendrites. Furthermore, synaptic activity leads to a large increase in intracellular calcium

resulting in the activation of the calcium-dependent enzyme calpain (Kaila 1998). eIF4E

is a calpain substrate and calpain-mediated cleavage of eIF4E inhibits cap-dependent translation (Nevins, Harder et al. 2003). Luckily, there is an alternative mechanism

utilized by eukaryotes to initiate translation.

In the nervous system, numerous dendritically localized mRNAs that are

translated in the dendritic spines contain IRESes including those encoding for the alpha subunit of CAMKII, activity-related cytoskeletal protein, and the neurotrophin receptor

TrkB (Pinkstaff, Chappell et al. 2001; Dobson, Minic et al. 2005). An IRES in the 5’

leader of a dendritically localized mRNA could recruit ribosomes and ensure efficient

translation after cleavage of eIF4E (Gingras, Gygi et al. 1999). eIF4G, like eIF4E, is a calpain substrate. However the proteolytic cleavage products of eIF4G can upregulate

IRES-dependent translation (Gabel, Won et al. 2004). These factors, along with the high

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preponderance of dendritically localized mRNAs containing IRESes suggest that IRES-

dependent translation is an important protein synthesis mechanism in dendrites.

As previously stated, the FMR1 mRNA is localized to neuronal dendrites and

localized translation of the mRNA is important for synaptic plasticity (Jin and Warren

2000). In addition, the 5’ leader of the FMR1 mRNA is both long and G/C rich. Together

these facts indicate a possible IRES in the 5’ leader of the FMR1 mRNA. In this study I

confirmed the presence of an IRES in 5’ leader the FMR1 mRNA in agreement with a

previous study (Chiang, Carpenter et al. 2001). Furthermore, I identified cis-elements in

the FMR1 5' leader critical for IRES activity and determined that FMR1 IRES activity is

affected by cellular processes in which FMRP participates.

Initially, the FMR1 5' leader was re-examined for IRES activity using dicistronic

DNA constructs. It was determined the leader contained a cryptic promoter, compelling the use of RNA constructs. Translation assays using RNA both in vitro and ex vivo demonstrated that the FMR1 5' leader does contain an IRES and that IRES-dependent

translation may be an important mechanism for the synthesis of FMRP in vivo. A

dissection of the 5' leader showed that the 5' 45 nucleotides (nt) as well as the CGG

repeats are important for internal initiation. Finally, multiple cellular stimuli including exposure to KCl and intracellular acidification as models for neural activity and exposure to polyinosinic:polycytidylic acid as a model for the presence of double stranded RNA

resulted in alterations of FMR1 IRES activity.

The FMR1 IRES: Future Directions

I would like to study the FMR1 IRES in a context more consistent with its natural

setting. The translation of the FMR1 mRNA may not be accurately portrayed by only

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studying the 5’ leader upstream of a reporter construct. Regulation of FMRP expression

in dendrites would not depend exclusively on the 5’ leader of the FMR1 mRNA. As

previously mentioned, FMRP itself interacts with the 3’UTR of the FMR1 mRNA and

this interaction can either repress or enhance to translation. Although these experiments

support the hypothesis that IRES-dependent translation contributes to the translation of

the FMR1 mRNA, they did not demonstrate the affect of the IRES on endogenous FMRP

expression. In other words, evidence of an IRES in the 5’ leader of a reporter construct

does not directly demonstrate the physiological relevance of that IRES in its natural

context. It merely indicates a possibility. This argument is one of the main critiques for

studying IRESes. So how do we identify the role of the IRES in translation of FMR1

mRNA?

One of the main mechanisms of translational regulation of dendritically localized

mRNA involves the protein encoded by the FMR1 mRNA- FMRP. FMRP utilizes

mRNA circularization to hide transcripts from trans-activating factors in its dual role as a

repressor and enhancer of protein synthesis. FMPR binds the 3’UTR of specific mRNAs,

including the FMR1 mRNA. FMRP also directly interacts with eIF4E (Jin and Warren

2000; D'Hulst and Kooy 2009). Through these interactions the target mRNA is

circularized and recruitment of eIF4G and the ribosome are prevented thereby inhibiting

translation initiation (Tamanini, Meijer et al. 1996). In addition, the FMRP-target mRNAs are protected from degradation suggesting circularization by FMRP interactions can indirectly enhance protein synthesis. How FMRP jumps between these dual roles is unknown. The FMRP- cytoplasmic FMR1 interacting protein 1 (CYFIP) repressor complex is known to dissociate with target mRNAs in response to synaptic stimuli

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allowing for de novo protein synthesis in dendrites (Siomi, Siomi et al. 1993; Willemsen,

Bontekoe et al. 1996). This complex is also thought to circularize mRNA, both

inactivating translation and protecting it from degradation. However circularization from

this complex is formed by the direct interaction of CYFIP, not FMRP, with eIF4E via a non-canonical binding site. How the complex interacts with the 3’end of the mRNA is unclear. FMRP could be binding the 3’UTR while in complex with CYFIP. Poly (A) binding protein (PABP) is another possibility since it is often found associated with the

FMRP-CYFIP complex (D'Hulst and Kooy 2009). Again, the mechanism that leads to the

dissociation of this complex is unknown. FMRP is differentially phosphorylated when in

the translationally inactive mRNP complexes versus in association with polysomes

(D'Hulst and Kooy 2009) so perhaps the phosphorylation state of FMRP changes in

response to different neurotransmissions thereby releasing a specific subset of target mRNAs from a repressed state to a translationally active one.

Regulation of translation of the FMR1 mRNA involves both the 5’ leader and the

3’ UTR. An approach to better determine the physiological relevance of FMR1 IRES

activity would be to test the IRES using a monocistronic RNA reporter construct that

contains both the FMR1 5’ leader and 3’ UTR. With this construct the reporter will be

able to interact with FMRP. Of course an m7G cap will be required since FMRP interacts

both directly and indirectly with eIF4E. To discern between cap-dependent and IRES-

dependent translation a hairpin downstream of the cap structure will be needed to inhibit

cap-dependent translation. Inserting a hairpin is essential to inhibit cap-dependent translation but it could also affect the IRES since cis-elements are at the 5’ end.

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To determine if a hairpin upstream of the FMR1 5’ leader affects IRES activity create a monocistronic RNA construct with the hairpin, FMR1 5’ leader, ApppG cap and a poly (A) tail. Compare translation of this construct to a similar one but without the hairpin. If the hairpin has no affect on the IRES the level of translation from these two constructs should be similar. If the hairpin does affect IRES activity adding a linker between them could resolve the issue.

After successfully creating this construct the next step would be to replace the

ApppG cap with an m7GpppG cap. If the hairpin inhibits cap-dependent translation adding a canonical cap should not negatively affect translation of this construct. From here add the 3’ UTR of the FMR1 mRNA downstream of the reporter ORF so that you have a construct containing the FMR1 5’ leader, FMR1 3’UTR, a hairpin that inhibits cap-dependent translation but does not affect the IRES, a m7G cap and poly (A) tail.

Although this construct is not the endogenous FMR1 mRNA it does put the IRES in a more natural context compared to the previous dicistronic RNA construct.

With this construct comparisons can be made to determine how the IRES functions in this setting. For all the following set of experiments, normalize activity of the reporter gene to transcript levels instead of a cotransfection. This method allows for comparisons between different cell lines or different cellular conditions. Compare translation of this construct to a similar one but minus the hairpin, so that both cap and cap-independent translation are possible to demonstrate the potential contribution of

IRES activity to overall translation of the FMR1 mRNA. To determine if any affect observed from the addition of the 3’UTR is dependent on the canonical cap, replace the m7G cap with the ApppG cap on both reporters and repeat the experiments. Additionally,

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look for any affects on IRES activity in response to neuronal stimuli under normal

conditions or with aberrant FMRP expression. Results from these experiments could lead to questions that can be tested in dendrites such as: Is potential usage of the IRES higher in dendrites than in cell lines? Is there any affect on potential IRES activity in response to neuronal stimuli in dendrites?

Understanding the Physiological Role of the FMR1 IRES in Neuronal Dendrites

Past studies of dendritically localized mRNAs containing IRESes used dicistronic

DNA constructs encoding for two different fluorescent genes that were transfected into primary hippocampal neurons. The construct contained a dendritic targeting element

(DTE) in the 3’UTR to localize the dicistronic transcript to the dendrites for translation of both cistrons. The upstream gene, translated cap-dependently, would encode a protein

(usually red fluorescent protein (RFP) or cyan FP (CFP)) with a nuclear localization signal allowing the protein to be sequestered to the nucleus. Fluorescent activity from this protein would be used to normalize for transfection efficiency. Sequestering it to the nucleus limits interference when measuring expression of the downstream cistron

(usually green FP (GFP)), translated by the IRES in the dendrites.

Using DNA reporters to test translation of the FMR1 5’ leader will first require testing for cryptic promoter activity. This activity was present in a dicistronic reporter with Renilla which contains numerous transcription factor binding sites that contribute to cryptic promoter activity. Using fluorescent encoding cistrons could eliminate this problem. Additionally a dual monocistronic DNA construct could be tried. Using a

separate promoter, a cap-dependent control monocistronic message, and the IRES-

dependent message contain the hairpin, FMR1 5’ leader and FMR1 3’UTR could be

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transcribed. FMR1 mRNA is targeted out to the dendrites via sequences in the 3’ UTR

(Antar, Afroz et al. 2004) so additional DTEs should not be needed for this reporter. It

will be necessary for the FMR1 3’UTR to be placed downstream of the control reporter

because in addition to the DTEs it contains elements that regulate mRNA stability. This

dual monocistronic construct allows for a nuclear experience, an internal control for

transfection efficiency, and testing a transcript that more closely resembles the

endogenous FMR1 mRNA. Potential cryptic promoter activity for the monocistronic

DNA reporter will need to be addressed prior to transfecting neurons to ensure the hairpin

sequence isn’t eliminated.

The last question I want to address is why are the CGG repeats evolutionarily

conserved in mammals (Eichler, Kunst et al. 1995)? The CGG repeats do promote IRES-

dependent translation of the FMR1 5’ leader (see Figure 3.4). Additionally, evidence

indicates that mRNA containing the normal number of CGG repeats translates at a higher

level compared to mRNA absent of the repeats (Jin, Zarnescu et al. 2003). However a

higher number of repeats leads to decreased translation (Chen, Tassone et al. 2003). Is the

contribution of the CGG repeats in a normal allele to the translation of the FMR1 mRNA essential for proper regulation of FMRP expression?

The monocistronic RNA construct with the hairpin could be used to determine the number of CGG repeats that maintain the highest amount of FMR1 IRES activity. I would predict the optimal number of repeats that support IRES activity will be within the normal range (5-60) since translation is affected once the repeats are in the pre-mutation

range. (Chen, Tassone et al. 2003). To test this I would transfect neurons with DNA (dual

monocistronic or dicistronic , depending on the result from the previous set of

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experiments) and compare translation from leaders +/- the CGG repeats, +/- the hairpin

(if using monocistronic reporters), and determine if the CGG repeats effect IRES activity

in response to a neuronal stimulus such as glutamate.

Is Targeting Aurora A Kinase Activity a Good Idea for Cancer Treatment?

The Aurora A kinase is a therapeutic target in cancer. Progress has been made in understanding Aurora A’s function in cancer development. Given its critical role in mitosis, many small-molecule inhibitors targeting Aurora A kinase activity are already in development and are involved in clinical trials (Mountzios, Terpos et al. 2008; Kitzen, de

Jonge et al. 2010). Unfortunately this method of anticancer treatment has to overcome major caveats including both drug delivery and target specificity.

The three Aurora kinases have overlapping function and structures. The most highly conserved region between the three family members happens to be the catalytic domain (Kollareddy, Dzubak et al. 2008). As a result, the first small-molecules developed to target Aurora A were pan-kinase inhibitors (Keen and Taylor 2004). Success with the

Aurora family inhibitors has been mixed. These therapies aren’t effective on their own so the general consensus is combination therapy is most likely necessary. Unfortunately,

with combination therapy comes the increased risk of toxicity since multiple small-

molecule inhibitors could increase inhibition of additional off-target kinases (Lee, Frolov

et al. 2006). Additionally, targeting Aurora A kinase activity may not be the best

approach. Over-expressing a kinase-dead mutant (T288A) Aurora A protein can cause

chromosomal instability (Kollareddy, Dzubak et al. 2008). A recent study demonstrated

that unphosphorylated Aurora A can still be catalytically active when bound to the

mitotic spindle by TPX2. Aurora A catalytic activity bound to TPX2 increases 15-fold

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(Dodson and Bayliss 2012). Therefore, the phosphorylation state of Aurora A is an

inaccurate indicator for its activity and targeting the catalytic domain may be ineffective.

Alternate approaches need to be considered for treating patients with Aurora A

over-expressing cancers. It has been shown that inhibiting Aurora A expression results in

apoptosis (Hata, Furukawa et al. 2005). I have shown Aurora A expression can be

regulated via an IRES. Additionally, IRES activity of two out the three IRES elements is increased in cells over-expressing the protein compared to normal cell lines. Targeting

Aurora A expression versus kinase activity may prove to be less toxic to non-cancerous

cells especially if a cancer specific mechanism is found. Another advantage to targeting

expression instead of activity is this method would eliminate any unknown function of

unphosphorylated Aurora A protein.

An Argument for Studying Activity of the Aurora A IRESes

Increased Aurora A kinase expression is proposed to contribute to cellular

immortalization (Kollareddy, Dzubak et al. 2008). However, the events that contribute to

enhanced Aurora A expression during early cancer development are still unclear. My

goal was to identifying these mechanisms with the intention to provide novel methods to

target Aurora A over-expression in tumors. Originally, the primary mechanisms

contributing to Aurora A over-expression in cancer were DNA-mediated translocation,

amplification, and transcription. The Aurora A gene is located on the 20q13 chromosomal

region and is often amplified in tumors resulting in increased Aurora A mRNA and

protein expression (Tanner, Tirkkonen et al. 1994; Tanner, Tirkkonen et al. 1995;

Bischoff, Anderson et al. 1998; Zhou, Kuang et al. 1998; Tanner, Grenman et al. 2000).

Additionally, there are many examples where Aurora A mRNA levels are increased

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without amplification, suggesting changes in transcription rate and/or mRNA stability

(Jiang, Katayama et al. 2010; Zhou, Kuang et al. 1998; Sakakura, Hagiwara et al. 2001;

Jeng, Peng et al. 2004; Tong, Zhong et al. 2004) (Jiang, Katayama et al. 2010; Zhou,

Kuang et al. 1998; Sakakura, Hagiwara et al. 2001; Jeng, Peng et al. 2004; Tong, Zhong

et al. 2004). Finally, translational regulation such as the rate of mRNA translation and

protein degradation can influence protein levels regardless of the mRNA level, indicating

the involvement of post-transcriptional mechanisms (Lai, Tseng et al. 2010; Taga,

Hirooka et al. 2009).

My study uncovered a non-DNA-mediated mechanism that contributes to

enhanced Aurora A expression in a subset of immortalized cell lines. IRES-dependent

translation of the 5’ leader of the Aurora A mRNA correlated with high levels of Aurora

A protein in these lines. In fact, IRES activity is the only mechanism leading to over-

expression of Aurora A protein in these cells. Interestingly, three of these lines are

immortalized but non-tumorigenic. This finding implicates misregulation of Aurora A

IRES activity could be exclusively responsible for increased Aurora A expression during

early tumor development. Additionally, this study suggests that synthesis of the Aurora A

protein is much more complex than just an increase in transcription. Why would a cell need nine different transcripts encoding for the same protein? Why the need for three

IRES elements? How does translation of the various transcripts contribute to the regulation of Aurora A expression in the G2/M phase of the cell? Indeed there are many questions yet to answer. I think my work has demonstrated that answering these questions could potentially lead to new therapeutics for cancer treatment, but even more than, that I think studying how Aurora A protein expression is regulated by these various elements

217

could change our perception on the importance of regulating gene expression at the level

of protein synthesis.

The Aurora A IRESes: Future Directions and Final Thoughts

I propose the following model for the misregulation of Aurora A protein synthesis leading to immortalization. Under normal conditions, the cell controls Aurora A protein expression by regulation of transcription, translation initiation of the various transcripts and protein degradation. Aberrant upregulation of ERK and AKT signaling to leads to the enhanced accumulation of the PKM2 isoform which targets exon II containing transcripts to the polysome. Aurora A protein is overexpressed via IRES-dependent translation which results in immortalization of the cell (Figure 6.1).

In this report I have demonstrated that the Aurora A 5’ leaders differentially regulate cap-independent translation of an RNA reporter transcript. Exons in some leaders can initiate translation cap-independently but then lose this ability when present in another leader. One explanation for this change in IRES activity is the presence of uORFs. Exon II and exon IIa each contain a uORF. These uORFs are out of frame with both the Aurora A initiator codon and each other. The start codon of the exon II uORF is not in a strong Kozak sequence (CucAUGG versus RccAUGG). It is in frame with two stop codons, one in exon IIa and one just downstream of the ORF initiator codon. The stop codon in exon IIa is 36 nt upstream of the ORF start codon. Interestingly, the UA leader that contains both exon II and exon IIa did not demonstrate IRES activity even though both exons were shown to contain IRES elements. Perhaps IRES activity of the exon II element is abolished in the presence of exon IIa because of this stop codon.

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Figure 6.1 Proposed model for translational regulation of the Aurora A kinase In response to external stimuli the ERK/AKT/mTOR pathway is upregulated. This events signals for accumulation of the PKM2 isoform. PKM2 interacts with exon II containing Aurora A transcripts and targets them for translation. Aurora A protein expression is upregulated by IRES-dependent translation of the exon II IRES. Over-expression of the Aurora A protein leads to immortalization of the cell. Over time as additional contributing events occur, including continued upregulation of AKT/mTOR signaling, the immortalized cell will become tumorigenic.

219

In contrast, the start codon of the exon IIa is in good Kozak sequence (GcaAUGG). This

sequence is in frame with two stop codons also in exon IIa. The first stop codon is only 6

nt downstream from the uORF start codon. The second stop codon is further downstream

but still 51 nt upstream of the Aurora A ORF. Mutational analysis of the Aurora A leader could reveal how these uORF mechanistically regulate IRES activity of the exon II and exon IIa IRES elements.

Mutational analysis of these leaders could also reveal crucial secondary structure required for activity of the different IRES elements. Secondary structure has been shown to be important for all viral IRESes. For example, mutations that affect the secondary structure of the base of a specific stem loop in the foot and mouth disease virus (FMDV)

IRES dramatically decreases internal initiation by interfering with eIF4G binding

(Martinez-Salas, Lopez de Quinto et al. 2002). Secondary structure has also been demonstrated to be important for some eukaryotic IRESes. The RNA structure exhibited by the Apaf-1 5’ leader mediates the presentation of binding sites for ITAFs necessary for

IRES function (Mitchell, Spriggs et al. 2003). Structural changes could explain the variation of IRES activity between the different Aurora A 5’ leaders. For instance the addition of exon II on a leader containing exon Ib could cause a conformational change to

a crucial ITAF binding site, thereby inhibiting activity of exon Ib IRES activity.

The effect on Aurora A protein expression in response to siRNA targeting of the

IRES elements in combination or individually could be used to answer numerous

questions. Expression of Aurora A in primary lines appears to rely on cap-dependent

initiation more than IRES–dependent (see Figure 4.8) suggesting targeting the IRES

would not affect expression in normal cells. But would cap-dependent translation be able

220

to maintain upregulated Aurora A expression in immortalized cells if IRES activity was

inhibited? Is it possible to target the IRESes that are upregulated without affecting the

IRES that is activity in all the lines? Will targeting both the upregulated IRESes be

needed to downregulate Aurora A protein expression? Combining siRNA with polysome

analysis could determine if a different pool of variants are associated with the HMW

polysome after silencing each exon. Additionally measure activity of reporter could

demonstrate changes in expression of specific leaders in response to silencing others.

In addition to finding the important ITAF(s), there are many questions that remain regarding signaling pathways and Aurora A IRES activity (Figure 6.2). First, why does

EGF induction of one cell line upregulate Aurora A protein expression but have no effect in a different cell? What receptors, kinases and substrates are involved? Could phosphorylation of a specific residue be a biomarker for exon II IRES activity? Is this a general mechanism that can regulate other IRESes or is it specific to G2/M regulated

IRESes or is it specific to the Aurora A exon II IRES? What’s regulating the other two

Aurora A IRESes?

In response to my first question I want to point out that the breast epithelial lines in this study, with the exception of MCF-7 cells, showed increased Aurora A protein levels with no change or decreased levels of Aurora A mRNA compared to normal

HMECs. Recently, breast epithelial cell lines have been classified into 5 major subtypes

according to expression of specific receptors as well as certain cancer markers These are

the same subtypes used to classify breast carcinomas. MCF-7 cells are classified as

Luminal A which has the best prognosis of all the subtypes in terms of cancer survival

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Figure 6.2 Future directions for signaling pathways Kinase inhibitors can be used to determine which pathways are contributing to increased Aurora A protein expression (despite decreased mRNA levels) and exon II IRES activity in MCF12A cells after EGF induction. Additionally, changes in Aurora A protein stability need to be determined.

222

(Subik, Lee et al.2010). The Luminal A subtype is both estrogen receptor and

progesterone receptor positive. MCF12A and MCF10A immortalized breast epithelial

lines are basal subtype, which are more aggressive cancers compared to the Luminal

subtypes but as I’ve stated previously these lines are non-tumorigenic (Subik, Lee et al.

2010). This tumor subtype does not express ER, PR, or Her2 and are also known as triple negative breast cancers. Finally the 21T series cells are Her2 positive, meaning they over-

express Her2 but not the hormone receptors. I would like to investigate the differences in

Aurora A expression and IRES activity between the classifications. If IRES activity

contributes to over-expression in one type of tumor versus another, novel targets would

allow for specialized treatment of Aurora A over-expressing breast carcinomas according

to their subtype. In addition, testing panels of other types of cancer cell lines would be a

good idea because Aurora A is over-expressed in many different kinds of tumors.

There is a lot of work ahead to identify what receptors, kinases and substrates are

involved in regulating exon II IRES activity (Figure 6.2). I found that EGF induction in

MCF12A cells leads to an increase in phosphorylation of AKT residue S473 but T308

phosphorylation decreased. The effect on downstream AKT substrates was also unexpected. With some like p27 there was no change, yet phosphorylation of other targets including GSK3a/b did increase (see Figure 5.9). Perhaps this specificity is the

result of the change in ratio between phosphorylation of S473 to T308.There is evidence

in the literature to support this possibility. For instance, under endoplasmic reticulum

(ER) stress T308 is suppressed while S473 is increased (Yung, Charnock-Jones et al.

2011). Also phosphorylation of T308, not S473, correlates with AKT activity in non-

small cell lung cancer (Vincent, Elder et al. 2011). Interestingly, phosphorylation of these

223

AKT residues in MCF12A and MCF10A cells under normal growth conditions again

show high p-S473 but low p-T308. I would like to look at phosphorylation of these

residues in the other cell lines tested. Should a correlation of increased exon II IRES

activity and this ratio between p-S473 and pT308 be determined, I would measure changes of Aurora A IRES activity and/or protein expression in cells expressing AKT mutants. Additional experiments with enhanced or repressed PKM2 would determine if

AKT is upregulating exon II IRES expression by PKM2.

I did demonstrate IRES activity of the original Aurora A 5’ leader was

upregulated during G2/M in synchronized HeLa cells (see Figure 4.7C). There are

signaling events that have been proposed to upregulate IRES activity during the G2/M

phase of the cell cycle. Novel phosphorylation sites have been identified on mTOR

complex 1 (mTORC1), the raptor protein. Cyclin-dependent kinase 1 (ckd1) and

glycogen synthase kinase 3 (GSK3) pathways have been implicated in phosphorylation of

these mTORC1 sites during G2/M specifically, resulting in altered mTORC1 activity

(Ramirez-Valle, Badura et al. 2010). This is an interesting finding since GSK3

phosphorylation is increased and therefore inactivated in response to EGF induction in

MCF12A cells when at least the exon II IRES is enhanced. Additionally knockdown of

GSK3 or CDK1 (CDC2) had no effect on the P:R ratio from the original Aurora A 5’

leader in the siRNA screen (see Appendix C).

There are many other possibilities that could affect activity of one or all three

Aurora A IRESes. Enhanced phosphorylation of eIF2α, increased expression eIF4G,

increased caspase-cleaved or protease 2A cleaved eIF4G, increase expression of the

eIF4G family member -death-associated protein 5 (DAP5), and decreased levels of

224 dyskerin have been linked to upregulating activity of various cellular and viral IRESes

(Kim, Park et al. 2011; Montanaro, Calienni et al. 2010; Lomakin, Hellen et al. 2000;

Han and Zhang 2002; Lewis, Veyrier et al. 2007). It would be interesting to see if the three Aurora A IRESes are regulated by any of these conditions. However, even though these examples have each been shown to regulate a handful of IRESes none have been shown regulate them all.

In fact, the hunt is on to find a general mechanism that regulates cellular IRESes.

I am not convinced this is the right direction for the field. This list provided above demonstrates the many different mechanisms that have already been found. None of them have been tested on more than a few IRESes yet there are grandiose predictions of their relevance in terms of general regulation of IRES activity. I think the better way to demonstrate how these mechanisms regulate IRES activity is to test a set of IRESes that encode genes with common functions, or are upregulated at similar times instead of testing one IRES and maybe EMCV and then speculate it will regulate other IRESes without testing them. I predict we will find different mechanisms that each regulate a set of cellular IRES, perhaps by activating a family of ITAFs in a manner similar to activating transcription factors. This is why I thought looking at signaling events might shed light on what was contributing to the upregulation of the Aurora A IRESes in immortalized cells.

Personally, I’m more interested in studying the regulatory mechanisms of specific cellular IRESes. One of my goals with the Aurora A IRES study was to find specific regulators of Aurora A IRES activity to target as an anti-cancer therapeutic, so for me the more specific the better. Additionally, if the specific mechanism is known questions

225 regarding the function of an IRES could be investigated. That being said I appreciate the desire to look for more general mechanisms in terms of basic science. Also some sort of commonality between these cellular IRESes would be exciting. However, I think the chance of finding similarities between cellular IRESes increases by focusing on their unique characteristics.

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APPENDIX A

PRIMER SETS

Cloning Primer Sets Aurora A 5’ leader FORWARD: 5’ GCT CTT GGA AGA CTT GGG TCC 3’ REVERSE: 5’ CAT GCC CAT TGG ATG CCT CGG CCT CCC AAA ATG C 3’ Aurora A variant search: 5’ FORWARD: 5’ ACA AGG CAG CCT CGC TCG AGC 3’ end REVERSE: 5’ CCT GAA ATG CAG TTT TCT TAA G3’ Aurora A variant search: 5’ FORWARD: 5’ GCT CTT GGA AGA CTT GGG TCC 3’ internal REVERSE: 5’ CCT GAA ATG CAG TTT TCT TAA G3’ tV6 FORWARD: 5’ GCT CTT GGA AGA CTT GGG TCC 3’ REVERSE: 5’ CAT GCC ATG GGA TGC CTC G3’ tV3, tV5 FORWARD: 5’ GCT CTT GGA AGA CTT GGG TCC 3’ REVERSE: 5’ CAT GCC CAT TGG ATG CCT CGG CCT CCC AAA ATG C 3’ tV4 FORWARD: 5’ GCT CTT GGA AGA CTT GGG TCC 3’ REVERSE: 5’ CAT GCC ATG GAT GCC CGT CGG CTC CC ACCT C3’ Unique A,B,and C FORWARD: 5’ GCT CTT GGA AGA CTT GGG TCC 3’ REVERSE 5’ ATG CCT GTA ATC CCA GCT AC 3’ qRT-PCR Primer Sets Aurora A ORF target FORWARD: 5′-TCT TCA CAG GAG GCA AAT CCA-3′ REVERSE: 5′-AAT AAG TTA CAC ACT CACT CAG GTA CTA-3′ Aurora A exon II target FORWARD: 5’ CAT TTG CCC AGG CGA FFC FAF AFT GCG 3’

Aurora A exon IIa target Gapdh target FORWARD: 5′-ACA GTC AGC CGC ATC TTC TT-3′ REVERSE: 5′ GTT AAA AGC AGCCC TGG TGA-3 Photinus target FORWARD: 5′-AAA GCT CCC AAT CAT CCA AA-3′ REVERSE: 5′-GAG ATG TGA CGA ACG TGT-3′

264

APPENDIX B

POLYSOME GRADIENTS

UV printout of sucrose gradients: Top Graph: MCF12A cells (blue) and MCF-7 cells (red) under normal growth conditions. Middle Graph: MCF12A cells +10 nM EGF (red) and –EGF (blue). Bottom Graph: MCF-7 cells +EGF 10 nM (red) and –EGF (blue).

265

APPENDIX C

SIRNA HUMAN KINASE/PHOSPHATASE LIBRARY SCREEN

Human Kinase Screen: Green Hit: Average Photinus activity:Renilla activity <.75 Red Hit Average Photinus activity:Renilla activity >1.5 siRNA P:R 1 P:R 2 P:R 3 Average RefSeq Nonsense 1.476854 1.505686 0.861893 Nonsense 0.686058 0.758711 1.017434 Nonsense 0.837088 0.735613 1.120679

CHKA 2.993293 1.116085 2.228352 2.112576 NM_00127 7

CHUK 2.409669 1.529928 2.91845 2.286016 NM_001278

CKB 2.357761 0.842052 1.584829 1.594881 NM_001823

CKM 1.40257 1.22981 1.072172 1.234851 NM_001824

CKMT1B 1.236736 0.858851 1.057051 1.050879 NM_020990

CKMT2 1.427163 0.780767 1.134862 1.114264 NM_001825

CLK1 1.805457 0.659265 1.029896 1.164872 NM_004071

CLK2 1.772916 1.447683 1.096249 1.438949 NM_003993

CLK3 1.187194 0.783335 0.966015 0.978848 NM_001292

PLK3 1.123993 0.841656 1.02809 0.997913 NM_004073

MAP3K8 1.424151 0.669815 0.99552 1.029829 NM_005204

MAPK14 0.860988 0.746953 0.917987 0.841976 NM_001315

CSF1R 0.823493 0.63099 1.182242 0.878908 NM_005211

CSK 0.681712 0.550833 0.906519 0.713022 NM_004383

CSNK1A1 0.607201 0.467315 0.973809 0.682775 NM_001025105

CSNK1D 0.735864 0.662255 0.770701 0.72294 NM_001893

CSNK1G2 0.728368 0.601003 0.820941 0.716771 NM_001319

CSNK1G3 0.530352 0.417718 0.803425 0.583832 NM_001031812

CSNK2A1 0.533106 0.588907 0.66904 0.597018 NM_001895

CSNK2A2 0.881707 0.631533 0.845878 0.786373 NM_001896

PDGFRL 1.011444 0.705872 0.879722 0.865679 NM_006207

RAGE 0.777493 0.76427 0.982509 0.841424 NM_014226

WEE1 0.658879 0.759752 0.864164 0.760931 NM_003390

MAST2 0.569035 0.523334 0.809946 0.634105 NM_015112

CDK6 0.581082 0.402403 0.822065 0.60185 NM_001259

CSNK1E 0.807736 0.531963 0.864078 0.734592 NM_001894

PLK2 0.774138 0.43398 0.94417 0.717429 NM_006622

NUAK1 0.653946 0.576591 0.751963 0.660833 NM_014840

PRKAA1 1.206491 0.411347 1.002208 0.873349 NM_006251

PIK3R4 1.157604 0.465349 1.223656 0.94887 NM_014602

TTK 0.775661 0.592509 0.932804 0.766991 NM_003318

NEK2 0.655809 0.527204 1.131084 0.771365 NM_002497

266

DCK 0.672679 0.428463 0.658876 0.586673 NM_000788

AURKA 0.483067 0.762422 0.814946 0.686811 NM_003600

CDK2 0.609027 0.496438 0.94639 0.683952 NM_001798

PRPS1L1 0.579928 0.589574 0.824036 0.664513 NM_175886

PRKD3 0.484471 0.48204 0.780609 0.582373 NM_005813

EPHB4 0.691462 0.528973 0.803745 0.674726 NM_004444

RIPK2 0.771838 0.51289 1.108618 0.797782 NM_003821 BUB1B 0.831203 0.422048 1.073088 0.775446 NM_001211 CDK10 0.658854 0.938465 1.108807 0.902042 NM_003674 BMPR1A 0.539493 0.420372 0.949113 0.636326 NM_004329 IP6K2 1.076704 0.616347 1.185838 0.95963 NM_001005909 IRAK1 0.599377 0.68669 0.929044 0.73837 NM_001025242 PGK1 0.735775 0.644665 0.903545 0.761328 NM_000291 MELK 0.787936 0.432321 0.775719 0.665325 NM_014791 PLK1 0.960878 0.539717 0.93262 0.811072 NM_005030

CDC2 0.843425 0.640073 0.94858 0.810693 NM_001786

AK1 0.935999 0.80174 0.889641 0.875794 NM_000476

COASY 0.713228 0.436967 0.829217 0.659804 NM_001042529

CHEK1 0.699521 0.592746 0.873038 0.721769 NM_001274

TK2 0.706241 0.723726 0.827236 0.752401 NM_004614

ATR 1.064446 0.525871 1.041249 0.877188 NM_001184

MAP4K3 0.919427 0.39262 0.844896 0.718981 NM_003618

DAPK3 1.029545 0.273728 0.790024 0.697766 NM_001348

EGFR 2.076274 0.484912 0.783937 1.115041 NM_005228

MAPKAPK2 1.883322 0.307304 0.929027 1.039884 NM_004759

ARAF 0.692782 0.457689 1.093411 0.747961 NM_001654

MATK 0.688863 0.44716 0.746501 0.627508 NM_002378

FRAP1 0.778939 0.517817 0.95793 0.751562 NM_004958

ERBB2 0.782611 0.689713 1.20462 0.892315 NM_001005862

RIOK2 1.116473 0.418484 0.89797 0.810975 NM_018343

AKT1 0.871903 0.367471 1.023726 0.754367 NM_001014431

PI4KA 0.622802 0.576372 1.196601 0.798592 NM_002650

SGK1 0.891697 0.64022 0.905625 0.812514 NM_005627

TBK1 1.647033 0.811121 0.883477 1.113877 NM_013254

PRKDC 0.793982 0.531043 0.810254 0.71176 NM_001081640

HIPK3 0.625422 0.396871 0.936233 0.652842 NM_001048200

ABL1 0.75363 0.54628 0.759916 0.686609 NM_005157

ABL2 0.675008 0.596912 0.931505 0.734475 NM_007314

ACVR1 0.429007 0.642518 0.639539 0.570355 NM_001105

ACVR1B 0.448559 0.907534 0.904824 0.753639 NM_004302

ACVR2A 0.878291 0.735428 1.233259 0.948993 NM_001616

ACVR2B 0.596636 0.290915 1.122743 0.670098 NM_001106

ACVRL1 0.789366 0.799055 0.815658 0.80136 NM_000020

267

ADK 1.11302 0.887858 0.698856 0.899911 NM_001123

ADRBK1 1.132651 0.558963 0.662432 0.784682 NM_001619

ADRBK2 0 0.656925 1.03771 0.564878 NM_005160

AK2 0.551135 0.565446 0.751021 0.622534 NM_001625

AK3L1 0.67792 0.626313 1.160153 0.821462 NM_001005353

AKT2 0.706666 0.787141 0.860109 0.784639 NM_001626

ALK 0.896586 0.498009 0.825729 0.740108 NM_004304

AMHR2 0.887963 0.527296 0.672816 0.696025 NM_020547

ATM 1.633477 0.765067 0.690219 1.029588 NM_000051

AXL 0.907643 0.538176 1.211845 0.885888 NM_021913

BLK 1.174177 0.518134 1.174817 0.955709 NM_001715

BMPR1B 0.810358 0.434381 0.808751 0.684497 NM_001203

BMPR2 1.209593 0.663815 0.809578 0.894329 NM_001204 Nonsense 1.306725 0.9069 1.323974 Nonsense 0.707157 0.970456 0.834256 Nonsense 0.986117 1.122641 0.93773 BMX 1.89028 5.595483 1.135394 2.873719 NM_001721

BRAF 1.951559 1.863461 1.312323 1.709114 NM_004333

BTK 1.360605 1.272264 1.482133 1.371667 NM_000061

BUB1 1.248857 1.120535 1.240265 1.203219 NM_004336

DDR1 0.984531 1.34079 1.155543 1.160288 NM_001954

CALM1 1.120342 1.301211 1.351836 1.257796 NM_006888

CALM2 1.021391 1.542416 1.20041 1.254739 NM_001743

CALM3 1.009563 1.560458 1.105871 1.225297 NM_005184

CAMK4 0.903456 0.78914 1.228566 0.973721 NM_001744

CAMK2A 0.921488 0.711767 1.344522 0.992592 NM_015981

CAMK2B 1.263308 0.618879 1.112774 0.99832 NM_001220

CAMK2D 0.945418 0.828361 0.828143 0.867307 NM_172115

CAMK2G 0.792178 0.515539 1.021005 0.776241 NM_001222

CD2 0.870374 0.593176 1.260069 0.907873 NM_001767

CDK11B 0.66207 0.609582 1.069656 0.780436 NM_033486

CDK3 1.022361 0.432957 1.078478 0.844598 NM_001258

CDK4 1.149031 0.685548 1.094901 0.976493 NM_000075

CDK5 1.154483 0.580581 1.121482 0.952182 NM_004935

CDK7 0.956805 0.588368 0.95785 0.834341 NM_001799

CDK8 0.903946 0.631296 0.918424 0.817889 NM_001260

CDK9 0.579979 0.753787 1.130191 0.821319 NM_001261

ILK 0.824206 0.536839 1.005529 0.788858 NM_001014794

INSR 0.614018 0.705862 1.053066 0.790982 NM_000208

INSRR 0.624361 0.693842 0.905097 0.7411 NM_014215

IRAK2 1.017321 0.540287 1.029091 0.862233 NM_001570

ITK 0.841286 0.694909 0.904243 0.81348 NM_005546

ITPK1 0.782177 0.496181 0.833277 0.703878 NM_014216

268

ITPKA 0.79112 0.92634 0.989746 0.902402 NM_002220

ITPKB 0.561874 0.638127 0.946952 0.715651 NM_002221

JAK1 0.575291 0.460211 1.028328 0.687943 NM_002227

JAK2 1.327481 0.42216 0.875044 0.874895 NM_004972

JAK3 0.737485 0.670672 0.961177 0.789778 NM_000215

KDR 0.839069 0.496413 1.131309 0.822264 NM_002253

KHK 0.646563 0.58909 0.876488 0.704047 NM_006488

KIT 0.804658 0.429002 0.994206 0.742622 NM_000222

NME5 0.860031 0.446663 1.09134 0.799345 NM_003551

PIP5K1A 1.01971 0.393612 1.580327 0.997883 NM_003557

PIP5K1B 1.100496 0.457348 0.850397 0.802747 NM_003558

PIP4K2B 0.729902 0.595545 0.894831 0.740093 NM_003559

ULK1 0.842603 0.786805 0.983244 0.870884 XM_001133335

STK24 0.646803 0.687339 0.900936 0.745026 NM_001032296

DYRK3 0.798772 0.54267 1.082759 0.808067 NM_001004023

DYRK2 0.634335 0.533345 0.933479 0.700386 NM_003583

DGKA 0.620946 0.581249 1.042903 0.748366 NM_001345

DGKB 0.75215 0.408366 0.745293 0.63527 NM_145695

DGKG 0.98097 0.433838 0.863293 0.759367 NM_001080744

DGKQ 0.946526 0.446437 0.938004 0.776989 NM_001347

DAPK1 0.837258 0.486807 0.823234 0.715766 NM_004938

DGUOK 1.202337 0.610326 0.892147 0.901603 NM_080916

DMPK 0.973216 0.695558 0.822814 0.83053 NM_001081560

DOK1 0.845277 0.260991 1.070005 0.725425 NM_001381

DTYMK 0.678107 0.583937 0.666281 0.642775 NM_012145

DYRK1A 0.980824 0.340134 1.081795 0.800917 NM_001396

EPHA2 1.037081 0.879071 1.153925 1.023359 NM_004431

MARK2 0.911752 0.89502 1.140173 0.982315 NM_001039468

EPHA1 0.569239 0.534636 0.772053 0.625309 NM_005232

EPHA3 1.041666 0.351611 1.320211 0.904496 NM_182644

EPHA4 0.647512 0.379332 0.901125 0.642656 NM_004438

EPHA5 1.707917 0.405682 0.854315 0.989305 NM_004439

EPHA7 0.84968 0.464471 1.17348 0.82921 NM_004440

EPHA8 0.730751 0.72803 1.478674 0.979152 NM_001006943

EPHB1 1.024207 0.799798 0.969218 0.931074 NM_004441

EPHB2 0.902791 0.502242 1.340989 0.915341 NM_004442

EPHB3 0.777605 0.570056 1.099101 0.815587 NM_004443

EPHB6 0.903195 0.556775 1.120698 0.860222 NM_004445

ERBB3 1.155648 1.217643 1.239704 1.204332 NM_001005915

ERBB4 1.028042 0.685404 0.836588 0.850012 NM_001042599

PTK2B 0.791352 0.529826 0.825086 0.715421 NM_004103

FER 0.816683 0.324014 0.87274 0.671145 NM_005246

FES 0.508745 0.408753 0.920795 0.612765 NM_002005

269

FGFR1 0.964063 0.326295 0.905175 0.731844 NM_015850

FGFR3 0.543136 0.588667 0.726287 0.619363 NM_000142

FGFR2 0.787395 0.53673 0.817873 0.713999 NM_022970

FGFR4 0.88837 0.515539 0.977205 0.793705 NM_002011

FGR 0.616667 0.553906 0.850147 0.673573 NM_001042729

FLT1 0.88142 0.607585 1.003201 0.830735 NM_002019

FLT3 0.525541 1.222557 0.991575 0.913225 NM_004119

FLT4 0.244738 0.659418 0.64249 0.515549 NM_002020

FRK 0.460342 0.79149 0.65917 0.637001 NM_002031

FYN 0.658139 0.466054 0.589657 0.571283 NM_002037

GAK 0.576591 0.713685 0.839508 0.709928 XM_001127411

GALK1 1.156659 0.446048 0.922896 0.841868 NM_000154

GALK2 0.970757 0.47782 0.718913 0.722496 NM_001001556

GCK 0.323222 0.579822 0.837495 0.58018 NM_033507

GCKR 0.450921 0.825437 0.831584 0.702647 NM_001486

GK 0.636921 1.237048 1.007295 0.960421 NM_203391

GK2 0.64866 0.836563 0.899785 0.795003 NM_033214

GRK4 0.507885 1.333489 0.727879 0.856417 NM_001004056 Nonsense 0.97202 0.968644 1.033852 Nonsense 0.955799 1.291158 1.000686 Nonsense 1.07218 0.740199 0.965627 GRK5 1.083151 3.254 1.91891 2.085354 NM_005308 GRK6 1.228847 1.559053 2.471037 1.752979 NM_001004106 MKNK2 1.183084 0.920043 1.630853 1.24466 NM_199054 GSK3A 0.89731 0.803732 1.51709 1.072711 NM_019884 GSK3B 0.849062 0.660626 2.119838 1.209842 NM_002093 GUK1 0.879634 1.613631 2.105531 1.532932 NM_000858 HCK 1.047879 1.113033 1.677073 1.279328 NM_002110 HK1 0.8658 0.995948 1.461456 1.107735 NM_033497 HK2 0.797498 0.938281 1.797687 1.177822 NM_000189 HK3 1.066848 1.162022 1.386469 1.205113 NM_002115 IGF1R 1.037466 0.816489 1.395242 1.083065 NM_000875 IKBKB 0.702784 0.887877 1.338655 0.976439 NM_001556 LCK 0.943736 0.668182 1.404405 1.005441 NM_001042771 LIMK1 0.78404 0.555409 1.339971 0.89314 NM_002314 LIMK2 0.886293 0.747874 1.305565 0.979911 NM_001031801 LTK 0.9355 0.576595 1.026311 0.846135 NM_206961 LYN 1.25087 0.822701 0.973238 1.015603 NM_002350 MAK 0.775707 0.457845 1.060509 0.764687 NM_005906 MARK1 0.783177 0.57022 1.474075 0.942491 NM_018650 MARK3 0.498198 0.819107 0.80376 0.707021 NM_002376 MAP3K1 0.998712 0.972027 1.28607 1.085603 XM_042066 MAP3K3 0.76451 8.348265 1.063921 3.392232 NM_002401

270

MAP3K4 1.021059 0.492979 0.674437 0.729492 NM_005922 MAP3K5 1.041842 0.482906 0.799727 0.774825 NM_005923 MET 0.913194 0.487325 1.075733 0.825418 NM_000245 SCGB2A1 0.949296 0.385565 0.771021 0.701961 NM_002407 MAP3K9 0.942998 0.506448 1.174444 0.87463 NM_033141 MAP3K10 0.694814 0.469452 0.867308 0.677191 NM_002446 MAP3K11 1.036538 0.48727 1.051994 0.858601 NM_002419 MOS 1.408364 0.677909 1.104478 1.063584 NM_005372 MPP1 0.941832 0.543895 1.457068 0.980931 NM_002436 MPP2 1.489639 0.538629 0.887201 0.971823 NM_005374 MPP3 1.111413 0.707198 0.967321 0.928644 NM_001932 MST1R 1.930579 0.472529 0.790196 1.064435 NM_002447 MUSK 1.125704 0.35775 0.743036 0.742163 NM_005592 MVK 1.414049 0.425011 0.921455 0.920172 NM_000431 MYLK 1.580294 0.423703 1.012267 1.005421 NM_053025 NEK1 1.3013 0.460072 0.93539 0.898921 NM_012224 NEK3 0.849228 0.52805 0.905567 0.760948 NM_002498 NME1 1.16944 0.483751 0.815804 0.822998 NM_000269 NME2 1.311858 0.312565 0.876071 0.833498 NM_001018137 NME4 1.074716 0.463116 1.153832 0.897221 NM_005009 NRGN 1.097389 0.761761 1.198227 1.019126 NM_006176 NTRK1 1.273504 0.62744 0.882199 0.927714 NM_001007792 NTRK2 1.118393 0.378331 0.805061 0.767262 NM_001007097 NTRK3 1.295576 0.348969 0.739108 0.794551 NM_001007156 ROR1 1.250755 0.476378 0.687726 0.804953 NM_001083592 ROR2 0.943947 0.335738 0.726738 0.668808 NM_004560 DDR2 1.102828 0.403779 0.882192 0.796266 NM_001014796 PAK1 0.914332 0.433629 0.669802 0.672588 NM_002576 PAK2 1.552122 0.726516 0.884562 1.0544 XM_001126110 PAK3 0.918738 0.477077 0.830415 0.742077 NM_002578 PCM1 1.048813 0.518215 1.086243 0.884424 NM_006197 PCTK1 1.52596 0.580787 0.87526 0.994002 NM_033018 PCTK2 0.770712 0.728262 0.813051 0.770675 NM_002595 PCTK3 0.878406 0.621441 0.697592 0.73248 NM_002596 PDGFRA 0.837895 0.541351 0.67393 0.684392 NM_006206 PDGFRB 2.630782 0.522854 0.741944 1.298527 NM_002609 PDK1 1.047746 0.53546 0.678907 0.754038 NM_002610 PDK2 1.917494 0.348882 0.816491 1.027622 NM_002611 PDK3 1.220316 0.484427 0.651424 0.785389 NM_005391 PDK4 1.121574 0.486226 0.822386 0.810062 NM_002612 PDPK1 1.087084 1.046877 0.852817 0.995593 NM_002613 PFKL 0.876156 0.701777 0.777184 0.785039 NM_002626 PFKM 0.858857 0.536619 0.948699 0.781392 NM_000289

271

PFKP 1.545997 0.651087 1.046667 1.08125 NM_002627 CDK14 1.218328 0.465422 0.658319 0.78069 NM_012395 PGK2 1.000441 0.366926 0.992306 0.786557 NM_138733 PHKG1 1.088324 0.591283 0.636118 0.771908 NM_006213 PHKG2 1.488161 0.480851 0.904379 0.957797 NM_000294 PIK3C2A 1.820502 0.353063 0.972963 1.048842 NM_002645 PIK3C2B 1.168848 0.581338 1.121851 0.957345 NM_002646 PIK3C2G 1.162099 0.637356 0.765784 0.85508 NM_004570 PIK3C3 1.581853 0.668369 1.009337 1.08652 NM_002647 PIK3CA 0.967965 0.615652 0.897292 0.82697 NM_006218 PIK3CB 1.08919 1.36499 0.778054 1.077411 NM_006219 PIM1 0.791974 0.661543 0.857133 0.770217 NM_002648 PIK3CD 0.715654 0.493774 0.677835 0.629088 NM_005026 PIK3CG 1.319922 0.388651 0.756452 0.821675 NM_002649 PI4KB 1.030382 0.523989 0.777067 0.777146 NM_002651 PIP4K2A 0.82178 0.618996 1.175167 0.871981 NM_005028 PKLR 0.975165 0.214241 0.969355 0.719587 NM_181871 PKM2 1.415947 0.573714 0.665871 0.885177 NM_002654 PLXNA1 1.18086 0.593313 0.754207 0.842794 NM_032242 PLXNA2 1.578447 0.97519 0.65406 1.069232 NM_025179 PLXNB3 1.429 1.114478 0.689346 1.077608 NM_005393 PRKAA2 1.321714 0.694543 0.880763 0.965673 NM_006252 PRKACA 0.887974 1.107694 0.874488 0.956719 NM_002730 Nonsense 1.197204 0.777056 1.07202 Nonsense 1.00255 0.909401 0.906026 Nonsense 0.800246 1.313529 1.02196 PRKACB 1.34408 2.722077 1.007683 1.69128 NM_002731 PRKACG 1.138772 2.046966 1.136565 1.440768 NM_002732 PRKCA 1.469275 2.506523 1.367389 1.781062 NM_002737 PRKCB 0.675497 1.865671 0.9299 1.157023 NM_212535 PRKCD 0.76532 1.445238 1.015866 1.075475 NM_006254 PRKCE 1.151661 1.92893 1.238059 1.43955 NM_005400 PRKCG 1.664602 1.135671 1.755745 1.518673 NM_002739 PRKCH 2.484622 1.097622 1.085588 1.555944 NM_006255 PRKCI 0.803107 0.826929 0.957095 0.862377 NM_002740 PKN1 0.379915 0.976755 0.965896 0.774189 NM_002741 PKN2 0.698117 3.919937 0.995043 1.871032 NM_006256 PRKD1 0.613635 0.86122 0.791536 0.755464 NM_002742 PRKCQ 0.450566 1.001602 0.81783 0.756666 NM_006257 PRKCSH 0.327783 0.761903 0.842833 0.644173 NM_001001329 PRKCZ 0.458095 0.866962 1.043764 0.789607 NM_001033581 PRKG1 0.405101 0.729513 0.948068 0.694227 NM_006258 PRKG2 0.27725 0.91624 1.009761 0.734417 NM_006259

272

MAPK1 0.283445 0.964986 0.858928 0.702453 NM_002745 MAPK3 0.33034 0.689271 1.062251 0.693954 NM_001040056 MAPK4 0.769853 0.764598 0.904731 0.813061 NM_002747 MAPK6 0.413664 0.692446 0.809658 0.63859 NM_002748 MAPK7 0.492022 0.753368 0.90136 0.715583 NM_139034 MAPK8 0.178747 0.701214 0.816724 0.565562 NM_002750 MAPK11 0.079209 0.883456 0.847198 0.603288 NM_002751 MAPK9 0 0.773634 0.908997 0.560877 NM_002752 MAPK10 0.169644 0.656138 0.95033 0.592037 NM_138981 MAPK13 0.35758 0.67441 0.90999 0.647326 NM_002754 MAP2K1 0.243486 0.692708 0.828758 0.588317 NM_002755 MAP2K2 0.319635 1.064376 0.744312 0.709441 NM_030662 MAP2K3 0.592289 0.757151 0.754976 0.701472 NM_002756 MAP2K5 0.531707 1.042548 1.309458 0.961238 NM_002757 MAP2K6 0.491221 0.944573 1.013544 0.816446 NM_002758 MAP2K7 0.408136 0.703346 1.027257 0.712913 NM_145185 EIF2AK2 0.575898 1.175938 0.956412 0.902749 NM_002759 PRKX 0.298454 0.819733 0.857092 0.658426 NM_005044 PRKY 0.550127 1.042971 0.840488 0.811195 NM_002760 PRPS1 0.469921 1.06098 0.837662 0.789521 NM_002764 PRPS2 0.427827 0.853753 0.744194 0.675258 NM_001039091 PRPSAP1 0.302763 1.483122 0.7353 0.840395 NM_002766 PRPSAP2 0.343451 0.672187 0.890084 0.635241 NM_002767 PSKH1 0.283879 0.942539 0.963726 0.730048 NM_006742 PTK2 0.31055 0.774097 0.887871 0.657506 NM_005607 PTK6 0.376736 0.727864 1.103913 0.736171 NM_005975 PTK7 0.401346 0.963818 1.122033 0.829066 NM_002821 TWF1 0.663856 1.242637 0.70771 0.871401 NM_002822 ALDH18A1 0.40781 0.731897 0.772056 0.637254 NM_001017423 MAP4K2 0.495362 0.662059 0.87276 0.676727 NM_004579 RAF1 0.536077 0.783656 0.685121 0.668284 NM_002880 RET 0.405629 0.923951 0.774966 0.701515 NM_020630 GRK1 0.826817 0.980709 0.757961 0.855162 NM_002929 RNASEL 0.54269 0.794384 0.764725 0.7006 NM_021133 ROCK1 0.752066 0.901409 0.717663 0.790379 NM_005406 ROS1 0.014784 0.746773 0.996231 0.58593 NM_002944 RP2 0.111962 0.864961 0.872756 0.61656 NM_006915 RPS6KA1 0.540966 1.015846 1.036769 0.864527 NM_001006665 RPS6KA2 0.417541 0.744845 0.78829 0.650225 NM_001006932 RPS6KA3 0.513109 0.67063 0.841233 0.674991 NM_004586 RPS6KB1 0.288738 0.793002 0.935063 0.672268 NM_003161 RPS6KB2 0.434867 0.778208 0.914929 0.709335 NM_003952 RYK 0.312788 0.601904 1.045042 0.653244 NM_001005861

273

MAPK12 0.130302 1.186702 0.84093 0.719311 NM_002969 MAP2K4 0.176348 0.987152 1.015517 0.726339 NM_003010 SKP2 0.301273 1.303701 1.143378 0.916118 NM_005983 SRC 0.330618 0.654826 0.789795 0.591747 NM_005417 SRMS 0.248534 0.928561 0.901533 0.692876 NM_080823 SRPK1 0.557533 1.084997 0.970663 0.871064 NM_003137 SRPK2 0.169984 1.157687 0.822563 0.716745 NM_182691 NEK4 0.473703 1.723566 0.767507 0.988259 NM_003157 STK3 0.253635 0.617745 0.894236 0.588538 NM_006281 STK4 0.36763 0.557973 0.923236 0.61628 NM_006282 CDKL5 0.3911 0.950603 0.739583 0.693762 NM_001037343 STK10 0.246474 0.869699 0.844855 0.653676 NM_005990 STK11 0.249388 0.819798 1.088749 0.719312 NM_000455 AURKC 0.429433 0.69454 0.904031 0.676002 NM_001015878 SYK 0.530926 0.873344 1.155822 0.853364 NM_003177 TAF1 0.438796 0.67119 0.707305 0.605763 NM_138923 MAP3K7 0.233422 1.408768 1.160033 0.934074 NM_003188 TEC 0.033113 0.932278 0.858911 0.608101 NM_003215 TEK 0.525981 0.436401 0.699602 0.553995 NM_000459 TESK1 0.36703 0.911906 0.959165 0.746033 NM_006285 TGFBR1 0.343256 0.529231 0.839921 0.570803 NM_004612 TGFBR2 0.032328 0.734432 0.758552 0.508437 NM_001024847 TIE1 0.292273 0.675361 1.01802 0.661884 NM_005424 TK1 0.026405 0.874545 0.7863 0.562417 NM_003258 TPR 0.256569 0.984698 0.872278 0.704515 NM_003292 TXK 0.285346 1.265711 0.924631 0.825229 NM_003328 TYK2 0.429613 1.004688 0.838679 0.75766 NM_003331 TYRO3 0.051796 2.030342 1.153668 1.078602 NM_006293 Nonsense 1.105321 1.688584 0.99079 Nonsense 1.069483 0.710008 1.117612 Nonsense 0.825206 0.601419 0.891601 UCK2 1.62904 5.652302 3.30209 3.527811 NM_012474 VRK1 1.116914 2.73771 1.518945 1.79119 NM_003384 VRK2 1.282614 2.478899 0.81601 1.525841 NM_006296 YES1 1.264 2.409597 2.280279 1.984625 NM_005433 ZAP70 1.069428 1.194195 1.6436 1.302408 NM_001079 MAP3K12 1.382056 1.791755 1.413978 1.529263 NM_006301 MAPKAPK3 1.125 2.03514 1.677922 1.612687 NM_004635 TRRAP 0.842083 1.976869 1.090759 1.303237 NM_003496 CDC7 0.906142 0.785544 0.778992 0.823559 NM_003503 CDC42BPA 1.029252 0.571924 0.997278 0.866151 NM_003607 PIK3R3 1.189685 1.419858 1.176619 1.262054 NM_003629 IKBKG 1.434158 0.596471 0.849419 0.960016 NM_003639

274

DGKZ 1.11568 0.535942 0.725584 0.792402 NM_201532 DGKE 1.084287 0.590413 0.704089 0.79293 NM_003647 DGKD 1.238784 0.343197 1.109868 0.897283 NM_003648 CAMK1 1.083568 0.635243 0.889359 0.86939 NM_003656 MAPKAPK5 1.156795 0.645192 0.879836 0.893941 NM_003668 PDXK 1.053711 0.459815 0.842506 0.785344 NM_003681 MADD 0.84781 0.936826 0.95437 0.913002 NM_003682 MKNK1 0.837648 0.414273 0.739641 0.663854 NM_003684 CASK 1.05554 0.456871 0.868009 0.793473 NM_003688 STK16 0.763492 0.522951 0.994239 0.760227 NM_001008910 CDC2L5 1.156307 0.357795 0.759583 0.757895 NM_031267 SKAP1 1.150107 0.368963 0.700605 0.739892 NM_001075099 MAPKSP1 1.110058 0.321892 0.855816 0.762589 NM_021970 TNK1 0.985914 0.417688 0.844256 0.749286 NM_003985 RIPK1 0.888249 0.279067 0.710514 0.625943 NM_003804 RIOK3 1.031967 0.371893 0.838906 0.747589 NM_003831 DYRK4 0.938487 0.685895 0.752661 0.792348 NM_003845 CDKL1 0 0.433805 0.859303 0.431036 NM_004196 KSR1 0.72235 0.501188 0.980613 0.734717 NM_014238 PIM2 0.839069 0.49473 1.051256 0.795018 NM_006875 CIT 0.792542 0.570639 0.940309 0.76783 NM_007174 MAP4K5 1.009275 0.380522 0.620285 0.670027 NM_006575 MAP4K1 1.178315 0.365018 0.91137 0.818235 NM_001042600 STK19 0.865419 0.382752 0.955477 0.734549 NM_004197 SPHK1 1.152659 0.357338 0.808681 0.772893 NM_182965 PRPF4B 1.193769 0.223219 0.957452 0.79148 NM_003913 RPS6KA4 1.453868 0.118216 0.71016 0.760748 NM_001006944 CDKL2 1.46982 0.416929 0.829546 0.905432 NM_003948 MAP3K14 0.912503 0.347657 0.82251 0.694223 NM_003954 BRSK2 0.9663 0.24933 0.817176 0.677602 NM_003957 PAPSS2 0.865518 0.321455 1.108264 0.765079 NM_001015880 PAPSS1 1.047918 0.297957 0.831495 0.72579 NM_005443 MAP3K6 1.431054 0.351147 0.749312 0.843838 NM_004672 LATS1 0.942229 0.277376 0.607425 0.60901 NM_004690 HGS 0.913148 0.217832 0.88324 0.671406 NM_004712 DYRK1B 1.043373 0.267117 0.71426 0.674917 NM_004714 DGKI 1.211865 0.378663 0.785363 0.791964 NM_004717 MAP3K13 0.678481 0.389241 0.955853 0.674525 NM_004721 DCLK1 0.98242 0.313934 0.7882 0.694851 NM_004734 AURKB 1.844756 0.39288 0.865939 1.034525 NM_004217 MAGI1 0.716383 0.51078 0.719305 0.648823 NM_001033057 RPS6KA5 1.042372 0.755834 0.904265 0.900824 NM_004755 MFHAS1 0.747067 0.417957 0.740272 0.635099 NM_004225

275

STK17B 1.002272 0.52239 0.705861 0.743508 NM_004226 STK17A 0.983704 0.49075 0.648142 0.707532 NM_004760 TAOK2 0.932574 0.533551 0.642435 0.702853 NM_004783 MAP4K4 0.99364 0.337217 0.775045 0.701967 NM_004834 EIF2AK3 1.256247 0.444975 0.718777 0.806666 NM_004836 PICK1 1.057659 0.546205 0.697068 0.766977 NM_001039583 AKAP7 1.058682 0.438204 1.043995 0.84696 NM_004842 SH3BP5 1.147808 0.410849 1.009309 0.855989 NM_001018009 ROCK2 1.224554 0.450746 0.898531 0.857944 NM_004850 CDC42BPB 0.751874 0.346069 0.716705 0.604883 NM_006035 AKAP12 1.175957 0.399636 0.921306 0.8323 NM_005100 AATK 1.446181 0.606618 0.615235 0.889345 NM_001080395 IKBKE 1.270523 0.715232 0.545934 0.843896 NM_014002 ULK2 1.230496 0.41987 0.979312 0.876559 NM_014683 SLK 0.846875 0.312334 0.746627 0.635279 NM_014720 IP6K1 1.064582 0.656187 0.834294 0.851688 NM_001006115 DNAJC6 1.051358 0.446207 0.748836 0.7488 NM_014787 MAGI2 1.205691 0.50553 0.716868 0.809363 NM_012301 TLK1 1.534639 0.589159 1.288625 1.137475 NM_012290 MRC2 0.893948 0.639672 0.8192 0.784273 NM_006039 XYLB 1.190652 0.631954 0.610995 0.8112 NM_005108 OXSR1 1.163983 0.367325 1.19215 0.907819 NM_005109 AKT3 1.31781 0.832861 0.881271 1.010648 NM_005465 GNE 0.82937 0.823888 1.54384 1.0657 NM_005476 COL4A3BP 1.137199 0.32229 1.465989 0.975159 NM_031361 SGK2 1.117504 0.432816 1.053001 0.867774 NM_016276 LRPPRC 1.216149 0.409566 4.504905 0.812857 NM_133259 PLXNC1 0.750614 0.805037 5.641685 0.777826 NM_005761 TNK2 1.401296 0.367381 10.40817 0.884338 NM_001010938 NME6 1.241054 0.52695 8.628927 0.884002 NM_005793 TRIB1 0.99422 0.806253 10.33566 0.900236 NM_025195 CNKSR1 1.177698 0.671375 12.30819 0.924537 NM_006314 AKAP8 1.058168 0.684158 9.684617 0.871163 NM_005858 Nonsense 1.098533 1.643414 1.08395 Nonsense 1.087767 0.587598 0.875469 Nonsense 0.813689 0.767939 1.040619 BCKDK 1.198026 1.957141 1.351884 1.502351 NM_005881 PAK4 0.718151 1.003208 1.298721 1.006694 NM_001014831 TESK2 1.182881 0.784022 0.991387 0.986096 NM_007170 MERTK 1.166246 0.860167 0.875526 0.967313 NM_006343 STK25 1.281586 0.940291 1.267255 1.163044 NM_006374 CIB1 1.171914 0.938659 1.085215 1.065263 NM_006384 ERN2 1.068392 0.973672 1.25464 1.098901 NM_033266

276

CAMKK2 0.892729 0.887511 1.227549 1.002596 NM_006549 PMVK 0.999817 0.594497 1.001941 0.865418 NM_006556 PLK4 1.019761 0.78014 1.166563 0.988822 NM_014264 MAP3K2 0.929821 0.641019 0.8089 0.793246 NM_006609 NEK6 0.956532 0.512855 1.057908 0.842432 NM_014397 FASTK 1.306085 0.385918 1.129786 0.940596 NM_006712 TLK2 0.95953 0.386892 1.310611 0.885677 NM_006852 RIPK3 1.126261 0.515646 1.184205 0.942037 NM_006871 CHEK2 0.963152 0.50477 1.027547 0.831823 NM_001005735 IRAK3 1.170886 0.459724 1.140851 0.92382 NM_007199 PACSIN2 1.085351 0.287334 1.239004 0.870563 NM_007229 MPP6 1.257932 0.396138 1.149186 0.934419 NM_016447 NLK 0.680665 0.471294 1.299826 0.817262 NM_016231 CMPK1 1.438931 0.497653 0.892077 0.942887 NM_016308 CRKRS 1.324099 0.260976 1.110656 0.898577 NM_016507 MST4 1.224452 0.361727 0.975573 0.853918 NM_001042452 ZAK 1.042828 0.373678 1.177692 0.864733 NM_016653 PANK1 0.904717 0.438944 1.344501 0.896054 NM_138316 FGFRL1 1.02304 0.305092 1.297617 0.87525 NM_001004356 CSNK1G1 1.128772 0.374286 1.197606 0.900221 NM_022048 RIPK4 1.040608 0.380305 0.74141 0.720774 NM_020639 SNRK 0.898795 0.315425 1.161211 0.79181 NM_017719 PXK 0.951779 0.367756 1.147751 0.822429 NM_017771 UCKL1 1.174667 0.2787 1.321022 0.924796 NM_017859 ULK4 1.02485 0.349005 1.164723 0.846193 XM_929989 PNKP 0.842294 0.467929 1.195929 0.835384 NM_007254 STK38 0.912139 0.402349 1.189959 0.834816 NM_007271 TWF2 1.206008 0.403006 1.016879 0.875298 NM_007284 AAK1 0.921495 0.379677 1.213482 0.838218 NM_014911 LMTK2 0.865576 0.373139 1.414366 0.88436 NM_014916 ICK 1.387811 0.429087 1.370554 1.062484 NM_014920 MAST1 1.343189 0.313777 1.148002 0.934989 NM_014975 STK38L 1.042163 0.42531 1.143955 0.870476 NM_015000 MAST3 1.111737 0.442321 1.28161 0.945223 XM_038150 TNIK 0.893161 0.416163 1.209677 0.839667 NM_015028 SMG1 0.944275 0.756906 1.067149 0.922777 NM_015092 CDK19 1.086638 0.540791 1.013951 0.88046 NM_015076 MAP3K7IP2 1.322826 0.270993 1.380575 0.991465 NM_015093 PLXND1 0.939699 0.249102 1.062423 0.750408 NM_015103 PASK 1.041495 0.31559 1.253072 0.870052 NM_015148 SIK2 1.066226 0.294364 1.373036 0.911209 NM_015191 ATMIN 1.055236 0.390037 1.192455 0.879243 NM_015251 PIP5K1C 0.994688 0.207087 1.179898 0.793891 NM_012398

277

TTC33 0.896773 0.45661 0.774264 0.709216 NM_012382 CCRK 1.142484 0.254297 1.06194 0.819574 NM_012119 DAPK2 1.147391 0.347729 1.424693 0.973271 NM_014326 ZMYND8 1.03775 0.281545 1.091081 0.803459 NM_012408 TSSK2 1.803246 0.624424 1.087176 1.171615 NM_053006 PLXNB2 1.0381 0.455459 0.925991 0.806516 XM_371474 SH3BP4 1.025445 0.337968 1.194009 0.852474 NM_014521 SGK3 1.293112 0.359372 1.269777 0.974087 NM_001033578 SHPK 1.172582 0.345718 1.20628 0.908193 NM_013276 DSTYK 1.022019 0.402348 1.188984 0.871117 NM_015375 PRKD2 1.177055 0.339472 1.17498 0.897169 NM_001079880 ULK3 1.29729 0.360718 1.167009 0.941673 XM_001134013 DAK 1.107158 0.407084 1.187587 0.90061 NM_015533 STAP1 1.294884 0.431757 1.335199 1.020613 NM_012108 AK5 1.200999 0.447603 1.22297 0.957191 NM_012093 LATS2 1.118876 0.911241 1.196886 1.075668 NM_014572 SRPK3 0.830097 0.420231 0.98376 0.744696 NM_014370 RPS6KC1 1.13203 0.384072 1.261464 0.925855 NM_012424 AKAP8L 1.203423 0.305538 1.330858 0.946606 NM_014371 TPK1 1.023009 0.381034 1.037934 0.813992 NM_001042482 EIF2AK1 1.070447 0.25005 1.110378 0.810292 NM_014413 STK36 0.844073 0.353091 1.223369 0.806844 NM_015690 ITGB1BP3 0.922376 0.339696 1.147806 0.803292 NM_014446 RPS6KA6 1.128354 0.330663 1.141222 0.866746 NM_014496 STK39 1.209203 0.416728 1.247698 0.957876 NM_013233 TRIB2 0.954211 0.362429 1.07305 0.796563 NM_021643 HIPK2 1.027673 0.751952 1.08054 0.953389 NM_022740 PACSIN3 0.798953 0.293569 0.986041 0.692854 NM_016223 EEF2K 0.990905 0.380859 1.135793 0.835852 NM_013302 NME7 1.297333 0.485767 1.18995 0.991017 NM_013330 PKN3 1.358229 0.588109 1.286941 1.07776 NM_013355 NRBP1 1.484554 0.561326 1.065306 1.037062 NM_013392 PACSIN1 0.836828 0.524824 1.210878 0.85751 NM_020804 HUNK 0.926061 0.323073 1.05069 0.766608 NM_014586 MINK1 0.865584 1.661327 1.140778 1.222563 NM_153827 AK3 1.402985 0.723487 1.108693 1.078388 NM_016282 TNNI3K 1.344447 0.669423 0.989081 1.000984 NM_015978 IRAK4 1.173483 1.331146 1.090768 1.198466 NM_016123 Nonsense 1.061211 1.432207 1.024743 Nonsense 1.113596 0.702264 0.931449 Nonsense 0.825206 0.86554 1.043831 VRK3 1.091758 1.762946 1.328016 1.39424 NM_001025778 CRIM1 1.019522 2.02961 1.205064 1.418065 NM_016441

278

CDKL3 0.761584 1.19608 1.371685 1.109783 NM_016508 TXNDC3 0.705993 0.91181 1.16228 0.926694 NM_016616 TAOK3 0.888397 1.101697 0.908629 0.966241 NM_016281 ZC3HC1 0.848297 0.9475 0.929269 0.908356 NM_016478 AURKAIP1 0.600649 1.027774 0.992774 0.873732 NM_017900 ETNK2 0.684762 0.949714 0.982361 0.872279 NM_018208 PANK4 1.002733 0.783747 0.924242 0.903574 NM_018216 PI4K2B 0.920971 0.882452 1.063135 0.95552 NM_018323 RFK 0.863392 1.745955 0.901905 1.170417 NM_018339 STK32B 0.904414 0.858118 1.014518 0.925683 NM_018401 STYK1 0.9001 1.185199 1.104668 1.063322 NM_018423 PI4K2A 0.701293 0.716294 1.318492 0.912026 NM_018425 STRADB 0.921346 0.685057 1.258098 0.954834 NM_018571 RIOK1 0.948749 1.478885 0.949646 1.12576 NM_031480 GSG2 0.768572 0.641213 0.91846 0.776082 NM_031965 STK40 0.834896 0.904989 0.791719 0.843868 NM_032017 TSSK1B 1.074282 1.319197 1.054175 1.149218 NM_032028 TSSK6 0.924534 1.437337 1.054656 1.138842 NM_032037 CAMKK1 0.872997 0.98623 1.197935 1.019054 NM_032294 BRSK1 0.943981 0.787455 0.892604 0.87468 NM_032430 0.924534 0.914992 0.902914 0.914147 NM_032435 TTBK1 1.055659 0.725855 1.27103 1.017515 NM_032538 CAMK2N1 0.846737 0.695862 1.014485 0.852361 NM_018584 ETNK1 0.727637 0.755779 1.228449 0.903955 NM_001039481 PLXNA3 0.826051 0.745594 1.234039 0.935228 NM_017514 CDC42BPG 0.790191 0.808762 1.214962 0.937972 NM_017525 NAGK 0.663683 0.911475 0.955703 0.84362 NM_017567 BMP2K 0.85432 1.201912 0.969685 1.008639 NM_017593 SCYL2 1.006475 0.949616 1.263891 1.073327 NM_017988 AGK 1.221117 0.894806 0.984095 1.03334 NM_018238 PBK 0.884194 0.94718 0.949221 0.926865 NM_018492 TEX14 0.943322 0.833383 1.026317 0.934341 NM_031272 SPHK2 1.388517 0.689964 0.92679 1.001757 NM_020126 PAK6 0.912524 0.604094 1.242062 0.91956 NM_020168 CDC42SE2 0.728024 0.708587 1.25202 0.89621 NM_001038702 CAMK1D 0.817694 0.871793 1.25674 0.982076 NM_020397 PAK7 1.316668 0.717036 1.070545 1.03475 NM_020341 SCYL3 1.200743 0.591609 1.227028 1.00646 NM_181093 CAMK1G 1.234246 0.957902 1.008927 1.067025 NM_020439 CLK4 1.006704 1.328924 1.304657 1.213428 NM_020666 SCYL1 1.080662 0.713112 0.989132 0.927635 NM_001048218 ALPK3 0.993097 0.749433 0.957966 0.900165 NM_020778 TAOK1 1.140293 0.548801 0.97582 0.888305 NM_020791

279

TRIB3 1.149093 0.69318 0.978097 0.940123 NM_021158 MARK4 1.157127 0.574266 1.103633 0.945009 NM_031417 LY6G5B 1.166392 0.557011 1.119413 0.947605 NM_021221 MPP4 1.007916 0.81093 1.029314 0.949387 NM_033066 TSKS 1.327598 0.432221 1.263669 1.00783 NM_021733 RBKS 1.01277 0.710321 1.13598 0.953024 NM_022128 SNX16 0.881137 0.645379 0.90218 0.809565 NM_022133 FN3K 0.837635 0.710373 1.102157 0.883389 NM_022158 MPP5 0.831832 1.31478 0.949257 1.031956 NM_022474 IPPK 0.845679 0.70657 0.980342 0.844197 NM_022755 CERK 1.136315 0.675552 1.119505 0.977124 NM_022766 IQCH 1.264653 0.650131 1.081286 0.99869 NM_001031715 PINK1 1.182731 0.622635 1.111186 0.972184 NM_032409 CDK15 0.947866 0.887445 0.985767 0.94036 NM_139158 WNK1 1.039106 1.524007 1.425465 1.329526 NM_018979 NADK 0.936313 0.532804 1.299667 0.922928 NM_023018 WNK4 0.998653 0.703422 1.150743 0.95094 NM_032387 WNK3 1.006187 0.884879 1.099578 0.996881 NM_001002838 WNK2 1.059971 0.744617 1.076461 0.96035 NM_006648 STK33 0.857081 0.770259 1.214779 0.947373 NM_030906 CAMKV 1.142471 1.132111 1.015314 1.096632 NM_024046 PANK3 0.650534 0.602791 1.220566 0.82463 NM_024594 0.732043 1.245578 1.21116 1.062927 NM_024619 LRRK1 0.938868 0.518617 1.156627 0.87137 NM_024652 0.628643 0.698064 1.200056 0.842254 XM_370878 PIP4K2C 0.855056 0.604429 1.090589 0.850025 NM_024779 NEK11 0.907534 0.847652 1.087017 0.947401 NM_024800 DCAKD 0.871314 0.899164 1.041945 0.937475 NM_024819 ADCK4 0.949187 0.947087 1.120973 1.005749 NM_024876 PANK2 1.001476 0.645174 0.993925 0.880192 NM_024960 YSK4 0.730729 0.825477 0.870298 0.808835 NM_001018046 HKDC1 1.093758 0.781939 0.9185 0.931399 NM_025130 ALPK1 1.053851 0.447469 1.068995 0.856771 NM_025144 ITPKC 1.003154 0.470412 1.094401 0.855989 NM_025194 TRAF3IP3 0.910043 0.606584 1.098433 0.871687 NM_025228 GRIP2 0.976125 0.552303 1.162973 0.897133 NM_001080423 TSSK3 1.320272 1.036844 1.013129 1.123415 NM_052841 NUAK2 0.919121 0.856871 1.280777 1.018923 NM_030952 ADPGK 1.201316 0.942766 1.103849 1.082643 NM_031284 UCK1 0.659977 0.995009 1.307591 0.987526 NM_031432 RPS6KL1 1.054854 0.841941 1.41677 1.104522 NM_031464 MASTL 1.279402 1.125211 0.914944 1.106519 NM_032844 MYLK2 1.060585 0.927015 1.01449 1.000697 NM_033118

280

Nonsense 1.083335 1.300439 1.049089 Nonsense 0.911456 0.755524 0.983449 Nonsense 1.005207 0.944036 0.967456 DCLK3 3.25109 2.348456 1.826498 2.475348 XM_940612 PSKH2 1.809382 2.548765 1.725781 2.027976 NM_033126 TPD52L3 1.631704 1.599903 1.282592 1.504733 NM_001001875 ADCK2 1.313341 2.229957 1.362484 1.635261 NM_052853 NEK9 1.436666 1.551613 1.55385 1.514043 NM_033116 MYLK3 1.175511 1.628641 0.927527 1.243893 NM_182493 STRADA 1.047877 1.359511 1.251159 1.219516 NM_001003788 PRKCDBP 1.140095 1.702066 1.256585 1.366249 NM_145040 LMTK3 0.811892 2.202714 0.955726 1.323444 NM_001080434 STK11IP 0.923165 0.912751 1.070634 0.96885 NM_052902 SLAMF6 1.058753 1.630576 1.268397 1.319242 NM_052931 ALPK2 1.122208 1.291346 0.995835 1.136463 NM_052947 IP6K3 0.904131 1.055685 0.909503 0.95644 NM_054111 PIK3AP1 0.835441 1.439247 0.892208 1.055632 NM_152309 LRRK2 0.614371 0.95824 0.965865 0.846159 NM_198578 CSNK1A1L 0.571924 0.884014 1.045395 0.833777 NM_145203 AK7 0.608753 0.977523 1.075571 0.887282 NM_152327 UHMK1 0.769233 0.983734 0.889412 0.880793 NM_175866 CIB4 0.773719 1.017695 1.137523 0.976312 NM_001029881 ACVR1C 1.350248 1.087042 1.04166 1.15965 NM_145259 GRK7 0.878718 1.140344 0.918423 0.979162 NM_139209 GLYCTK 0.923107 0.771078 0.982542 0.892242 NM_145262 ASB10 0.59871 0.704273 1.046256 0.78308 NM_080871 PIP5KL1 0.584987 0.837555 1.047833 0.823458 NM_173492 TAF1L 0.557744 0.615328 1.093239 0.755437 NM_153809 DGKK 0.57213 0.707124 0.991049 0.756768 NM_001013742 PNCK 0.699028 0.831263 0.875311 0.801867 NM_001039582 NEK7 0.728893 0.705023 1.111735 0.848551 NM_133494 STK35 0.820009 1.204549 0.967139 0.997232 NM_080836 MPP7 1.023257 0.811391 1.116939 0.983862 NM_173496 TTBK2 0.656082 1.124983 1.000542 0.927202 NM_173500 HIPK4 0.919225 0.949241 0.880067 0.916178 NM_144685 PDIK1L 0.721012 0.912963 1.003517 0.879164 NM_152835 SIK1 0.908552 0.701225 0.868153 0.825977 NM_173354 NEK10 0.647786 0.800087 0.91727 0.788381 NM_001031741 CNKSR3 0.712852 0.678736 0.860181 0.75059 NM_173515 AKAP14 0.615489 0.901984 1.010482 0.842652 NM_001008534 DGKH 0.654265 0.896653 0.936633 0.829184 NM_152910 DCLK2 1.026938 0.853824 0.93023 0.936997 NM_001040261 FUK 0.81457 0.758878 0.795956 0.789801 NM_145059

281

MLKL 0.731478 0.971202 1.06514 0.922607 NM_152649 STK32A 0.712297 0.865983 0.932371 0.836884 NM_145001 ADCK5 0.840477 0.878427 1.038329 0.919078 NM_174922 NRK 0.936778 1.069189 0.854254 0.953407 NM_198465 HIPK1 0.722226 0.538764 0.788055 0.683015 NM_152696 MAPK15 0.656249 1.168079 0.907713 0.91068 NM_139021 IPMK 0.538217 0.743495 0.997413 0.759709 NM_152230 ANKK1 0.737114 0.783885 0.85962 0.79354 NM_178510 GK5 0.705157 0.97565 1.147216 0.942674 NM_001039547 MAGI3 0.681483 0.770071 0.950845 0.8008 NM_152900 STK32C 0.528764 1.005926 1.073712 0.869467 NM_173575 KSR2 0.664374 0.895718 1.036636 0.865576 NM_173598 TSSK4 1.443475 0.945707 0.912039 1.100407 NM_174944 NEK8 1.324988 1.097811 0.922037 1.114945 NM_178170 EPHA6 1.273805 0.927866 1.008971 1.070214 NM_001080448 NRBP2 0.828452 0.655511 0.816574 0.766846 NM_178564 NEK5 0.795358 0.894059 0.974824 0.88808 NM_199289 CDKL4 1.171957 0.926815 1.058113 1.052295 NM_001009565 TXNDC6 0.574883 0.947294 1.005867 0.842681 NM_178130 SBK1 1.131479 0.851072 0.86301 0.94852 NM_001024401 MAP3K15 0.799183 0.965989 1.11415 0.959774 NM_001001671 PIM3 0.615053 0.71544 1.151182 0.827225 XM_938171 EIF2AK4 0.668382 0.563318 0.906758 0.71282 NM_001013703 NME3 0.57503 0.815217 0.954178 0.781475 NM_002513 PKMYT1 0.90745 0.745826 0.920798 0.858025 NM_004203 ERN1 0.710262 0.854549 0.913719 0.826176 NM_001433 EPHA10 0.680466 0.596787 0.847333 0.708195 NM_001004338 PLXNB1 0.622187 0.656618 0.798302 0.692369 NM_002673 SIK3 0.492327 0.576115 0.75353 0.607324 NM_025164 PION 0.566056 0.921472 0.88552 0.791016 NM_017439 C9orf95 0.848918 0.715375 0.964788 0.843027 NM_017881 FGGY 0.790657 0.637022 0.866059 0.764579 NM_018291 STAP2 1.002099 0.932274 1.137575 1.023983 NM_001013841 C21orf7 0.693684 0.858062 1.04705 0.866265 NM_020152 PTCD2 0.877041 0.765928 0.871097 0.838022 NM_024754 MORN1 0.699134 1.242236 0.925945 0.955772 NM_024848 SH3BP5L 1.031659 0.968137 0.950472 0.983422 NM_030645 C1orf57 1.883923 0.821537 0.958766 1.221408 NM_032324 IGFN1 0.842924 0.684178 1.048395 0.858499 NM_178275 PLXNA4 1.092325 0.838882 0.876269 0.935825 NM_181775 FLJ25006 0.706851 0.879473 0.923982 0.836769 NM_144610 0.778007 0.823185 0.794129 0.79844 XM_937796 C9orf98 0.972024 0.821778 0.947814 0.913872 NM_152572

282

MGC42105 0.875095 0.888556 1.053165 0.938938 NM_153361 C9orf96 0.701711 1.145589 1.189182 1.01216 NM_153710 IGSF22 1.061893 0.8886 0.87081 0.940434 NM_173588 MYLK4 1.28841 0.763461 1.114852 1.055574 NM_001012418 BMP2KL 1.412569 0.873294 0.864308 1.050057 XM_936694 Nonsense 1.440386 1.048653 0.962628 Nonsense 0.786794 0.973086 1.014118 Nonsense 0.772827 0.978262 1.023246 C19orf35 2.428186 1.284437 1.135226 1.61595 NM_198532 CERKL 0.58859 1.259637 0.830946 0.893058 NM_001030313 AK3L1 0.550711 1.23595 0.71654 0.834401 NM_001002921 0.596668 1.292262 0.788498 0.892476 XM_372002 0.393733 1.056925 0.712512 0.721056 XM_372705 PI4KAP2 0.809939 1.037804 0.945875 0.931206 NM_199345

Top Ten Potential Signaling Pathways regulating Aurora A IRES Actvity as determined by NIH DAVID program/ Kegg pathways

Top 10 Increased P:R P -

Term Genes Count % Value MAPK signaling pathway 8 32 4.6E-06 Vascular smooth muscle contract 5 20 0.00025 Long-term potentiation 4 16 0.00093 Chemokine signaling pathway 5 20 0.0018 Tight junction 4 16 0.0065 Non-small cell lung cancer 3 12 0.011 Vibrio cholerae infection 3 12 0.011 Glioma 3 12 0.014 Long-term depression 3 12 0.017 VEGF signaling pathway 3 12 0.02

283

Top 10 Decreased P:R P-

Term Genes Count % Value 1.1E-

MAPK signaling pathway 35 21.2 18 5.8E-

ErbB signaling pathway 20 12.1 15 7.9E-

GnRH signaling pathway 19 11.5 13 3.8E-

Fc epsilon RI signaling pathway 16 9.7 11 5.1E-

Neurotrophin signaling pathway 19 11.5 11 Progesterone-mediated oocyte 1.6E-

maturation 16 9.7 10 1.7E-

Toll-like receptor signaling pathway 16 9.7 09 1.8E-

Pathways in cancer 27 16.4 09 4.5E-

T cell receptor signaling pathway 16 9.7 09 2.2E-

Pancreatic cancer 13 7.9 08

Human Phosphatase Screen: Green Hit: Average Photinus activity:Renilla activity <.75 Red Hit Average Photinus activity:Renilla activity >1.5 siRNA P:R 1 P:R 2 P:R 3 Average RefSeq Nonsense 0.962077 1.094509 1.132042 Nonsense 1.08794 1.005949 0.989675 Nonsense 0.950004 0.899535 0.878289

PPP4R1 1.8854 1.460918 2.04859 1.798303 NM_001042388

PTPN12 1.285734 1.319844 1.800043 1.46854 NM_002835

PPP3R1 1.006765 1.067902 1.419552 1.16474 NM_000945

PTEN 0.992896 1.052934 1.767091 1.270974 NM_000314

PTP4A2 1.411428 0.910093 1.427442 1.249654 NM_080391

PPP2R2A 1.110546 1.027444 1.824956 1.320982 NM_002717

PTPN6 1.141666 1.10233 1.737249 1.327082 NM_002831

PPP1CC 1.073454 0.975622 1.110503 1.053193 NM_002710

G6PC3 0.873323 0.889289 1.190935 0.984516 NM_138387

ACP1 0.965514 0.916441 1.246732 1.042896 NM_004300

ACP2 1.100276 1.141807 1.503517 1.248533 NM_001610

284

ACP5 0.950091 0.922257 1.057194 0.976514 NM_001611

ACPP 0.77394 0.828077 1.174236 0.925418 NM_001099

ACYP2 1.00963 0.882438 1.03805 0.976706 NM_138448

ALPI 0.839838 0.85428 1.136082 0.9434 NM_001631

ALPL 0.970284 0.826411 1.025371 0.940689 NM_000478

ALPP 0.958851 0.734345 1.143601 0.945599 NM_001632

ALPPL2 1.115591 0.773997 1.396311 1.0953 NM_031313

ASNA1 0.805076 0.799285 1.075551 0.893304 NM_004317

ENTPD1 1.030028 0.794254 0.945481 0.923254 NM_001776

ENTPD2 0.998279 0.851295 0.999347 0.949641 NM_001246

ENTPD6 0.873467 0.809048 1.041272 0.907929 NM_001247

ENTPD3 0.692086 0.766492 0.912278 0.790286 NM_001248

ENTPD5 0.826613 0.688959 0.870264 0.795279 NM_001249

CDC25A 0.874011 0.770779 0.974386 0.873058 NM_001789

CDC25B 0.934543 0.801471 0.994406 0.91014 NM_004358

CDC25C 0.971447 0.727902 0.908887 0.869412 NM_001790

CDKN3 0.898701 0.733971 0.990205 0.874292 NM_005192

DUSP1 0.910189 0.731479 1.128195 0.923288 NM_004417

DUSP2 0.952167 0.675479 1.029684 0.885777 NM_004418

DUSP3 1.038228 0.855993 1.443774 1.112665 NM_004090

DUSP4 0.881526 0.82287 1.457445 1.053947 NM_001394

DUSP5 0.885015 0.881979 1.367411 1.044802 NM_004419

DUSP6 0.743524 0.830415 0.965525 0.846488 NM_001946

DUSP7 0.870709 0.693191 1.101429 0.888443 NM_001947

DUSP8 0.814767 0.728812 0.86544 0.803007 NM_004420

DUSP9 0.767471 0.706123 1.044956 0.839516 NM_001395

DUT 0.85248 0.832667 1.069766 0.918304 NM_001025248

FBP1 0.759299 0.693588 1.141318 0.864735 NM_000507

G6PC 0.833414 0.629352 0.955962 0.806243 NM_000151

HINT1 0.920387 0.906427 1.028585 0.9518 NM_005340

IMPA1 0.868699 0.760886 1.065423 0.898336 NM_005536

IMPA2 0.929006 5.814643 0.988009 2.577219 NM_014214

INPP1 0.80391 0.746057 1.094485 0.881484 NM_002194

INPP5A 0.940968 0.668889 0.990506 0.866787 NM_005539

INPP5B 0.819106 0.794814 0.782765 0.798895 NM_005540

INPP5D 0.822883 0.727236 0.664357 0.738159 NM_001017915

INPPL1 0.964293 0.710088 0.811742 0.828708 NM_001567

ITPA 0.890412 0.896004 1.024272 0.936896 NM_033453

MTM1 0.813928 0.974921 0.978463 0.922438 NM_000252

PPP1R12A 0.8177 0.707127 0.987735 0.83752 NM_002480

PPP1R12B 0.771607 0.834126 0.955459 0.85373 NM_032104

NAP1L1 0.831494 0.960654 1.204128 0.998759 NM_004537

NAP1L4 0.839229 0.732842 1.170739 0.91427 NM_005969

285

NT5E 0.837805 0.769681 1.011072 0.872852 NM_002526

OCRL 0.74318 0.71464 1.051203 0.836341 NM_000276

PFKFB1 0.817742 0.914935 0.984838 0.905838 NM_002625

PFKFB2 0.762906 0.717763 0.982002 0.82089 NM_001018053

PFKFB3 0.670983 0.806824 0.789579 0.755796 NM_004566

PFKFB4 1.024909 0.561618 0.866265 0.817597 NM_004567

PPA1 0.87533 0.654037 0.948531 0.825966 NM_021129

PPEF2 0.885241 0.832572 1.025235 0.914349 NM_006239

PPEF1 0.95681 0.781484 1.2651 1.001131 NM_006240

PPM1A 0.75481 0.721815 1.13787 0.871498 NM_177951

PPM1B 0.827152 0.927417 1.110057 0.954876 NM_001033556

PPM1G 0.968866 0.888327 1.266415 1.041203 NM_002707

PPP1CA 0.912847 0.71393 1.044162 0.890313 NM_001008709

PPP1CB 0.932546 0.888869 0.986479 0.935964 NM_002709

PPP1R1A 0.885948 0.764428 0.58385 0.744742 NM_006741

PPP1R2 0.796682 0.64538 0.736661 0.726241 NM_006241

PPP1R3A 0.910687 0.669539 0.637244 0.739157 NM_002711

PPP1R3C 0.733352 0.82899 0.720998 0.761113 NM_005398

PPP1R3D 0.742917 0.68172 0.928655 0.784431 NM_006242

PPP1R7 1.061457 0.84506 0.800821 0.902446 NM_002712

PPP1R8 0.713414 0.728125 0.743949 0.728496 NM_002713

PPP2CA 0.82507 0.691453 0.937242 0.817922 NM_002715

PPP2CB 0.872017 0.945296 0.861342 0.892885 NM_001009552

PPP2R1A 0.779646 0.507898 0.655165 0.647569 NM_014225

PPP2R1B 0.832119 0.642546 0.81572 0.763462 NM_002716

PPP2R2B 0.911857 0.822 0.834 0.855952 NM_004576

PPP2R2C 0.945994 0.744867 0.840857 0.843906 NM_020416

PPP2R3A 1.017892 0.978832 0.892152 0.962959 NM_002718

PPP2R4 1.054552 0.798972 0.677363 0.843629 NM_021131

PPP2R5A 1.011076 0.908029 1.113431 1.010845 NM_006243

PPP2R5B 0.607168 0.872831 1.017821 0.832607 NM_006244

PPP2R5C 0.660458 0.698204 0.869043 0.742568 NM_178588

PPP2R5D 0.866134 0.76759 0.961792 0.865172 NM_006245

PPP2R5E 0.973261 1.249409 0.924428 1.049032 NM_006246 Nonsense 0.995155 1.099168 1.151251 1.081858 Nonsense 0.949384 0.952096 0.960501 0.953994 Nonsense 1.055464 0.94875 0.888237 0.96415

PPP3CA 1.036607 1.285093 1.740612 1.354104 NM_000944

PPP4C 1.102903 1.259375 1.267699 1.209992 NM_002720

PPP3CB 1.106665 1.160937 1.550091 1.272564 NM_021132

PPP3CC 1.059905 1.152413 1.24433 1.152216 NM_005605

PPP3R2 1.168673 1.043454 2.291125 1.501084 NM_147180

PPP5C 1.001334 1.273016 1.492384 1.255578 NM_006247

286

PPP6C 1.342905 1.192105 2.610051 1.71502 NM_002721

PSPH 0.935049 1.291116 1.530795 1.25232 NM_004577

PTPN1 1.266203 1.323531 1.309254 1.299663 NM_002827

PTPN2 1.051834 1.079998 1.046404 1.059412 NM_002828

PTPN3 1.194282 1.169018 0.987399 1.1169 NM_002829

PTPN7 0.919337 0.937506 1.119337 0.99206 NM_002832

PTPN9 1.050929 0.849344 1.261786 1.05402 NM_002833

PTPN11 1.151438 1.090538 1.175307 1.139094 NM_002834

PTPN13 1.02673 1.180212 0.921186 1.04271 NM_080684

PTPN14 0.923402 0.995679 1.088093 1.002391 NM_005401

PTPRA 1.147203 1.269011 1.115955 1.17739 NM_002836

PTPRC 1.030136 0.96939 1.053094 1.01754 NM_002838

PTPRD 1.077658 1.007503 1.354567 1.146576 NM_001040712

PTPRE 1.092275 0.984493 1.166358 1.081042 NM_130435

PTPRF 1.178138 1.177005 0.962472 1.105872 NM_002840

PTPRG 0.961137 1.028921 0.95428 0.981446 NM_002841

PTPRH 0.868108 0.762654 0.839252 0.823338 NM_002842

PTPRJ 1.057053 0.617483 1.061308 0.911948 NM_002843

PTPRK 0.935436 0.880444 0.963735 0.926539 NM_002844

PTPRM 1.066338 0.941044 0.968468 0.99195 NM_002845

PTPRN 1.000613 0.799594 1.193208 0.997805 NM_002846

PTPRN2 0.984543 1.023129 0.842094 0.949922 NM_130843

PTPRO 1.107695 1.029794 0.899051 1.01218 NM_002848

PTPRR 1.082453 0.930962 0.80236 0.938592 NM_002849

PTPRS 1.138569 1.105725 1.148872 1.131055 NM_002850

PTPRZ1 1.101027 1.003341 1.348953 1.151107 NM_002851

SBF1 1.065645 1.06686 0.970222 1.034242 NM_002972

PPP1R11 0.883043 0.855585 0.848204 0.862277 NM_021959

TPTE 0.958721 0.899303 0.887512 0.915179 NM_199259

PTP4A1 1.024553 0.822702 0.931646 0.9263 NM_003463

EPM2A 0.896803 0.958964 1.010771 0.955512 NM_001018041

ANP32A 0.956679 0.782491 1.090944 0.943372 NM_006305

HDHD1A 0.994123 0.740264 0.776175 0.836854 NM_012080

DUSP11 1.023528 0.896787 0.83369 0.918002 NM_003584

PPM1D 1.116517 1.001778 1.151169 1.089821 NM_003620

CDC14B 1.161918 1.042168 1.055805 1.086631 NM_001077181

CDC14A 1.073804 0.952169 0.92026 0.982078 NM_033313

PPAP2A 0.95276 0.978804 1.361481 1.097682 NM_003711

PPAP2C 1.038039 0.799419 0.661855 0.833104 NM_003712

PPAP2B 0.965693 0.887912 0.689262 0.847622 NM_003713

RNGTT 1.245843 0.79227 0.871481 0.969864 NM_003800

MTMR1 1.036509 0.798494 0.741497 0.858833 NM_003828

FBP2 1.136488 0.685155 1.035991 0.952545 NM_003837

287

SYNJ1 1.025004 0.793126 0.868362 0.895498 NM_203446

SYNJ2 1.024795 0.783059 1.035843 0.947899 NM_003898

MTMR3 1.082039 0.748445 0.811238 0.880574 NM_153050

MTMR2 0.886359 0.972162 0.968725 0.942415 NM_016156

ATP6V0E1 1.100559 1.065574 1.049711 1.071948 NM_003945

MTMR6 1.134884 1.034609 0.994311 1.054601 NM_004685

MTMR7 0.911366 0.879891 0.867865 0.886374 NM_004686

MTMR4 1.056665 0.898778 0.788455 0.914633 NM_004687

CTDP1 0.996029 0.838456 0.87635 0.903612 NM_004715

MINPP1 1.178419 0.770834 0.984004 0.977753 NM_004897

ENTPD4 0.943309 1.044286 0.818224 0.935273 NM_004901

PPM1F 1.10635 0.821874 1.083525 1.003916 NM_014634

MFN2 0.991153 0.714412 0.936177 0.880581 NM_014874

PTPRU 1.03589 0.852586 0.89 0.926159 NM_005704

CTDSP2 0.986603 1.032877 0.934814 0.984765 NM_005730

CTDSPL 0.904411 0.801592 0.940459 0.882154 NM_001008392

BPNT1 0.925489 1.043563 0.89512 0.954724 NM_006085

CIB2 0.919645 0.769632 0.883511 0.857596 NM_006383

ANP32B 0.957697 0.734869 0.747406 0.813324 NM_006401

MTMR11 0.979807 0.891581 0.796706 0.889365 NM_181873

DUSP14 1.036743 0.797485 0.803918 0.879382 NM_007026

PTPN21 1.042685 0.705754 0.928514 0.892318 NM_007039

PTPRT 0.899904 0.780219 0.953931 0.878018 NM_007050

PTP4A3 0.957752 1.037968 0.938256 0.977992 NM_007079

NUDT4 0.970037 0.723945 1.020317 0.904766 NM_019094

NUDT5 1.041217 0.926888 0.756267 0.908124 NM_014142

NUDT3 1.214555 1.391493 1.022041 1.209363 NM_006703

DUSP10 0.888583 0.992625 0.921911 0.934373 NM_007207

CHP 0.900233 0.988129 0.923668 0.937343 NM_007236

DUSP12 1.140578 0.727685 0.912561 0.926941 NM_007240

PNKP 1.042596 0.831547 0.76685 0.880331 NM_007254

PPM1E 0.944001 0.891507 0.827089 0.887532 NM_014906

SAPS1 0.916894 0.981964 0.94533 0.948062 NM_014931

INPP5F 1.049274 0.975231 0.765317 0.929941 NM_014937

NT5C2 1.052407 1.209505 0.92233 1.061414 NM_012229

ANP32D 1.078277 1.077622 0.830111 0.995336 NM_012404

ANP32C 1.064596 0.996926 1.020025 1.027182 NM_012403

CABIN1 0.961225 0.895992 0.859329 0.905516 NM_012295

PTPN23 1.049386 1.147011 1.207074 1.13449 NM_015466

Nonsense 1.105298 1.035136 1.073887 1.07144

Nonsense 0.953085 0.898943 1.064569 0.972199

Nonsense 0.941622 1.065915 0.861522 0.956353

PPP1R16B 1.32427 1.164567 1.269126 1.252655 NM_015568

288

PTPN20B 1.624765 0.994892 1.269415 1.296357 NM_001042357

PTPN22 1.96967 0.820442 1.409513 1.399875 NM_012411 PTPN18 1.107546 0.897025 1.280409 1.094993 NM_014369 PPP1R14B 0.991697 1.16547 1.715588 1.290918 NM_138689 PPA2 0.974087 0.875818 1.749061 1.199655 NM_001034191 INPP5J 1.046453 1.714618 1.682433 1.481168 NM_001002837 PPP2R3B 1.186319 0.950009 1.215641 1.117323 NM_013239 ACP6 1.458744 0.922979 1.148083 1.176602 NM_016361 DUSP13 0.918163 1.105834 1.515366 1.179787 NM_001007271 STYXL1 1.081534 1.421809 1.438738 1.314027 NM_016086 INPP5K 0.846068 0.601359 1.038417 0.828615 NM_016532 SSH1 0.915662 0.861264 0.963205 0.913377 NM_018984 MTMR12 0.731393 0.711076 1.207406 0.883291 NM_001040446 PPM2C 0.763039 0.871678 1.204021 0.946246 NM_018444 PPP1R12C 0.838349 0.878053 1.071817 0.929406 NM_017607 PPP1R14D 0.995682 0.79998 0.943213 0.912958 NM_017726 MTMR10 0.703763 0.726054 1.004773 0.81153 NM_017762 DUSP23 0.890236 1.439073 1.192202 1.173837 NM_017823 SSH3 1.009819 1.432258 1.222148 1.221408 NM_017857 PPP2R3C 0.937703 0.852415 1.137266 0.975795 NM_017917 MTMR8 0.893392 1.32126 0.988419 1.06769 NM_017677 MFN1 0.761755 1.824451 1.106501 1.230902 NM_033540 PPP2R2D 0.658934 0.798799 1.129147 0.862293 NM_001003656 INPP5E 0.696264 1.747262 1.108982 1.18417 NM_019892 DUSP22 0.665832 1.140601 0.993213 0.933216 NM_020185 PDXP 0.83724 1.397188 1.243203 1.15921 NM_020315 ENTPD7 0.950563 1.099284 1.331292 1.127046 NM_020354 DOLPP1 0.710805 0.733423 1.243851 0.896026 NM_020438 PDP2 0.901728 0.842681 1.268208 1.004206 NM_020786 G6PC2 0.761767 0.810663 0.760012 0.777481 NM_001081686 CTDSP1 0.633555 0.9864 1.01757 0.879175 NM_021198 DUSP21 0.726237 1.196734 1.344952 1.089308 NM_022076 CHTF18 0.772798 0.785626 1.022066 0.860163 NM_022092 CHP2 0.597075 0.912894 0.917341 0.809104 NM_022097 LHPP 0.781628 0.86354 0.943594 0.862921 NM_022126 MTMR14 0.69173 0.932708 1.141944 0.922127 NM_001077525 LPPR2 0.722212 0.833399 1.310037 0.955216 NM_022737 TNS3 1.259393 0.87571 1.256025 1.130376 NM_022748 MTMR9 0.871067 0.914232 1.036264 0.940521 NM_015458 DUSP26 0.77183 1.263323 1.159197 1.064784 NM_024025 PPP1R3B 0.848219 0.867605 1.143079 0.952968 NM_024607 DUSP16 0.84497 1.075556 1.134576 1.018367 NM_030640 ILKAP 0.863054 1.003934 1.021488 0.962825 NM_030768

289

SGPP1 0.528909 0.970094 1.067842 0.855615 NM_030791 ANP32E 0.655854 0.688624 0.93488 0.759786 NM_030920 PPP1R14C 0.45236 0.768126 1.009474 0.74332 NM_030949 SBF2 0.734965 0.923457 1.03524 0.897887 NM_030962 PPP1R1B 0.445192 0.786744 1.183575 0.80517 NM_032192 PTPN5 0 0.893803 1.205608 0.699804 NM_001039970 PPP1R16A 0.661408 0.875845 1.115214 0.884156 NM_032902 SSH2 1.079431 0.825139 1.012528 0.972366 NM_033389 PPP1R3F 0.732905 0.79599 0.973965 0.834287 NM_033215 ACPL2 0.655508 0.859231 0.938379 0.817706 NM_001037172 TPTE2 0.539162 0.892611 0.946805 0.79286 NM_130785 ACPT 0.557054 1.022967 1.03775 0.87259 NM_033068 PPP1R14A 0.751781 0.740057 0.877324 0.789721 NM_033256 CIB3 0.461348 0.9573 0.923784 0.780811 NM_054113 CANT1 0.699148 0.727732 1.00676 0.811213 NM_138793 PPM1M 0.689189 0.848297 1.05846 0.865315 NM_144641 LRGUK 0.664594 1.023135 1.086482 0.924737 NM_144648 PTPDC1 0.721961 0.81542 1.033636 0.857006 NM_152422 DUSP19 0.725087 0.976311 0.975523 0.892307 NM_080876 DUSP18 0.647267 0.979863 1.183297 0.936809 NM_152511 PPM1L 0.720271 1.055655 0.9155 0.897142 NM_139245 PPM1K 0.882327 1.108743 1.245098 1.078723 NM_152542 PPTC7 0.720751 0.908028 0.975992 0.868257 NM_139283 CDC14C 0.768382 0.868402 0.875765 0.837516 XM_001125780 PPAPDC1A 0.740214 0.758999 1.064923 0.854712 NM_001030059 NUDT14 0.479476 0.827652 0.964554 0.757227 NM_177533 NAP1L5 0.61691 0.822246 0.893438 0.777531 NM_153757 DUSP28 0.696409 0.896864 0.973026 0.855433 NM_001033575 PPM1J 0.770957 1.011796 1.110448 0.9644 NM_005167 HDDC3 0.762268 0.666358 0.946308 0.791645 NM_198527 FLJ16165 0.766966 0.766269 1.148328 0.893855 NM_001004318 PTPN20A 0.659893 0.745179 1.104883 0.836652 NM_001042387 NUDT6 0.744894 0.854894 1.120594 0.906794 NM_007083 DUPD1 0.767599 0.576725 0.768651 0.704325 NM_001003892 ACYP1 0.585914 0.680182 0.861305 0.709133 NM_001107 FHIT 0.557601 1.026703 1.014884 0.866396 NM_002012 NAP1L2 0.684457 0.721316 1.128526 0.844766 NM_021963 NAP1L3 0.707738 0.643163 0.818645 0.723182 NM_004538 SET 0.791335 0.7516 0.952669 0.831868 NM_003011 TNS1 0.91451 0.9183 0.915888 0.916233 NM_022648 SAPS2 0.792626 0.737804 0.917668 0.816033 NM_014678 PHACTR2 0.82052 0.756468 1.010231 0.862407 NM_014721 LPPR4 0.790107 0.853575 1.116965 0.920216 NM_014839

290

FIG4 0.767619 0.853211 1.132722 0.91785 NM_014845 Nonsense 1.021332 1.047528 1.102218 1.057026 Nonsense 1.01874 0.86019 0.921452 0.93346 Nonsense 0.959949 1.092275 0.97634 1.009522

SACM1L 1.673424 2.898658 1.587683 2.053255 NM_014016

KIAA1274 1.309626 1.487073 1.379994 1.392231 NM_014431

LPPR1 2.195909 1.193804 1.412127 1.600613 NM_017753

IMPAD1 1.115464 1.598173 1.363143 1.358927 NM_017813

NUDT11 0.980702 1.453814 1.266107 1.233541 NM_018159

SAPS3 1.120307 1.699037 1.185924 1.335089 NM_018312

PPM1H 1.27556 1.114266 1.271147 1.220324 XM_350880

ENOPH1 1.248187 1.173483 1.553672 1.325114 NM_021204

PHACTR4 1.356589 1.130825 1.282584 1.256666 NM_001048183

LPPR3 1.03908 1.091217 1.21903 1.116442 NM_024888

HDHD2 1.194285 1.144093 1.029718 1.122699 NM_032124

PPAPDC1B 1.026804 1.005264 1.087484 1.039851 NM_032483

HINT2 0.998531 1.179952 1.098489 1.092324 NM_032593

PPAPDC3 1.130506 0.959131 1.051608 1.047082 NM_032728

RWDD2A 0.992124 0.978492 0.979693 0.983436 NM_033411

CCDC104 1.101212 1.288349 1.100475 1.163345 NM_080667

PHACTR3 1.191994 1.221316 1.107099 1.17347 NM_080672

SGPP2 0.801784 1.118444 1.18971 1.036646 NM_152386

FLJ40125 0.908994 1.036651 1.22267 1.056105 NM_001080401

CCDC155 0.963721 1.052232 0.980428 0.998794 NM_144688

PPP1R1C 1.113429 0.891531 1.171574 1.058844 NM_001080545

C3orf48 1.153637 0.955593 1.337952 1.149061 NM_144714

ATP6V0E2 0.858573 0.916034 1.041651 0.938752 NM_145230

LPPR5 0.995266 0.835762 0.921099 0.917375 NM_001010861

NUDT10 0.814018 0.716382 0.943667 0.824689 NM_153183

PHACTR1 0.990545 0.941466 1.215615 1.049209 NM_030948

NUDT8 1.157534 0.864475 1.080161 1.034057 NM_181843

PGP 0.884764 0.615255 1.112042 0.870687 NM_001042371

ENTPD8 1.0479 0.8461 0.970848 0.954949 NM_001033113

LOC389217 1.109321 1.036168 1.189565 1.111685 XM_371701

PPAPDC2 0.983146 1.079297 0.957977 1.006806 NM_203453

LOC441511 1.229822 1.094292 1.175627 1.166581 XM_937130

LOC441868 0.967083 1.108621 0.935882 1.003862 XM_497647

RWDD2B 0.844122 1.087459 0.945617 0.959066 NM_016940 No signaling pathways were detected

291

APENDIX D

HUMAN PHOSPHO-KINASE ARRAY

Membrane/Coordinate Target/Control Phosphorylation Site

A-A1, A2 Reference Spot ___

A-A3, A4 p38α T180/Y182

A-A5, A6 ERK1/2 T202/Y204, T185/Y187

A-A7, A8 JNK pan T183/Y185, T221/Y223

A-A9, A10 GSK-3α/β S21/S9

B-A13, A14 p53 S392

B-A17, A18 Reference Spot ___

A-B3, B4 MEK1/2 S218/S222, S222/S226

A-B5, B6 MSK1/2 S376/S360

A-B7, B8 AMPKα1 T174

A-B9, B10 Akt S473

292

Membrane/Coordinate Target/Control Phosphorylation Site

B-B11, B12 Akt T308

B-B13, B14 p53 S46

A-C1, C2 TOR S2448

A-C3, C4 CREB S133

A-C5, C6 HSP27 S78/S82

A-C7, C8 AMPKα2 T172

A-C9, C10 β-Catenin ___

B-C11, C12 p70 S6 Kinase T389

B-C13, C14 p53 S15

B-C15, C16 p27 T198

B-C17, C18 Paxillin Y118

A-D1, D2 Src Y419

A-D3, D4 Lyn Y397

A-D5, D6 Lck Y394

A-D7, D8 STAT2 Y689

293

Membrane/Coordinate Target/Control Phosphorylation Site

A-D9, D10 STAT5a Y694

B-D11, D12 p70 S6 Kinase T421/S424

B-D13, D14 RSK1/2/3 S380/S386/S377

B-D15, D16 p27 T157

B-D17, D18 PLCγ-1 Y783

A-E1, E2 Fyn Y420

A-E3, E4 Yes Y426

A-E5, E6 Fgr Y412

A-E7, E8 STAT3 Y705

A-E9, E10 STAT5b Y699

B-E11, E12 p70 S6 Kinase T229

B-E13, E14 RSK1/2 S221/S227

B-E15, E16 c-Jun S63

B-E17, E18 Pyk2 Y402

A-F1, F2 Hck Y411

294

Membrane/Coordinate Target/Control Phosphorylation Site

A-F3, F4 Chk-2 T68

A-F5, F6 FAK Y397

A-F7, F8 STAT6 Y641

A-F9, F10 STAT5a/b Y694/Y699

B-F11, F12 STAT1 Y701

B-F13, F14 STAT4 Y693

B-F15, F16 eNOS S1177

B-F17, F18 PBS (Negative Control) ___

A-G1, G2 Reference Spot ___

A-G5, G6 PBS (Negative Control) ___

Relative Pixel Density

Kinase Phos HMEC MCF-7 MCF12A MCF10A Ref Spot ___ 100000 100000 100000 100000 p38α T180/Y182 52313.3 27905.5 56223.74 59477.52 ERK1/2 T202/Y204, T185/Y187 86010.68 115381.1 120713.7 101602.5 JNK pan T183/Y185, T221/Y223 25249.81 25868.29 16521.57 1961.841 GSK-3α/β S21/S9 19448.95 5404.258 8438.882 2776.076 p53 S392 4157.297 90106 MEK1/2 S218/S222, S222/S226 4071.257 21198.68 12869.54 25241.28 MSK1/2 S376/S360 6179.237 41189.79 15350.92 8816.161 AMPKα1 T174 10753.95 Akt S473 69802.89 27459.86 111704.7 109203.4

295

Kinase Phos HMEC MCF-7 MCF12A MCF10A Akt T308 39175.58 7010.864 15510.87 p53 S46 17383.01 35131.75 12805.47 9656.662 TOR S2448 7066.036 5334.532 12076.8 37871 CREB S133 21305.66 72359.26 HSP27 S78/S82 16774.62 7331.217 12148.87 AMPKα2 T172 11866.68 29854.79 21276.93 5089.472 β-Catenin ___ 1789.241 19451.49 3662.894 2248.742 p70 S6 K T389 17383.01 15614.55 p53 S15 25374.96 49639.75 10116.67 25238.24 p27 T198 Paxillin Y118 Src Y419 3817.048 Lyn Y397 11888.76 5158.241 Lck Y394 11280.43 STAT2 Y689 5569.135 12260.63 13572.15 5718.837 STAT5a Y694 33503.78 7252.499 24773.67 27981.99 p70 S6 K T421/S424 53270.5 56692.17 5027.927 15496.72 RSK1/2/3 S380/S386/S377 31277.5 14036.12 21405.48 PLCγ-1 Y783 FYN Y420 4417.372 2686.629 18409.18 Yes Y426 6612.84 Fgr Y412 9906.123 STAT3 Y705 5602.378 5731.667 19153.91 28870.98 STAT5b Y699 42779.48 5902.444 28736.29 75573.3 p70 S6 K T229 42224.13 50036.88 21026.65 RSK1/2 S221/S227 25601.79 17747.75 12317.57 c-Jun S63 3193.258 16917.11 Pyk2 Y402 Hck Y411 7008.35 4025.6 12948.96 Chk-2 T68 6972.585 FAK Y397 6046.949 STAT6 Y641 16789.53 8377.207 26148.48 37343.67 STAT5a/b Y694/Y699 24855.79 7987.146 10384.9 18105.1 STAT1 Y701 25545.08 8964.319 5944.115 STAT4 Y693 19708.05 5665.983 7589.758 eNOS S1177 3240.189 6685.614 PBS(Neg) ___ Ref Spot ___ 51888.5 41661.5 42943 42261 PBS(Neg) ___

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